Scenario Analysis using System Dynamics M odelling:
The case of Production Portfolio C hange in the Dutch Paper
and Board Industry
C.M. Chiong Meza, G.P.J. Dijkema, C.E. van Daalen
Delft University of Technology, Faculty of Technology, Policy and Management
P.O. Box 5015, 2600 GA Delft, The Netherlands
015-2782727
C.M.ChiongMeza@tudelft.nl; G.P.].Dijkema@ tudelft.nl, C.vanD aalen@ tudelft.nl
Abstract
A scenario analysis on plausible futures served to explore the Dutch Paper and Board -
P&B - Industry's resilience towards competition in the form of an aggressive
investment from outside the current industry. A System Dynamics model helped to
visualize the effects on the Dutch industry's production portfolio. A scenario-space was
constructed by combining three mega trends - Demand-shift for P&B products, Social
awareness of recycling and Dutch business environment - and five alternative set-ups
of a new facility by the prospective competitor.
The model output reveals the dominance of the Demand-shift for P&B products,
reinforced by the Social awareness of recycling, for a good performance of the Dutch
P&B Industry, regardless of the new facility type. The Dutch business environment
offers limited scope to counterbalance the decreasing sales of P&B products.
Interestingly, this industry retains growing sales and profits patterns even in the worst-
case scenario.
The case study confirmed that the combination of scenario analysis and System
Dynamics could support the analysis and visualization of the effects of major,
competitive investments on a mature industry.
Keywords: Scenario Analysis, System Dynamics, Paper and Board, Industry,
Investment.
1. Introduction
The Dutch Paper and Board Industry - Dutch P&BI - is a successful, responsible and
mature industry that must operate in an increasingly competitive and dynamic
environment. It is an energy-intensive sector, where volatile and increasing energy
prices introduce substantial risk for eroding profits. Nowadays, the growing interest in
bio-energy has led to a dramatic increase of wood prices, the raw material for virgin
pulp-manufacture. Used paper exports have driven-up the prices for recycled paper, the
main Dutch P&BI’s feedstock. These and other trends may result in gradual changes of
the sector in the coming years.
A different scenario for this production sector may also become reality: the
emergence of a “nightmare competitor” (Thorpe, 2000) in the form of a new entrant to
the Dutch P&BI scene. A company that has enough financial resources and access to
state-of-the-art technology could design, build and operate a highly competitive new
facility for pulp and/or paper in the Netherlands by exploiting economies-of-scale,
innovative technology and system concepts. This is more likely as it may seem, since
mergers and acquisitions have resulted in a sector dominated by a few multinational
corporations. Intemational headquarters currently manage most of the Dutch P&BI
companies and only a limited number of the global pulp, paper and board conglomerates
are presently active in the Netherlands. Therefore, investments in the Netherlands
originating from outside the current Dutch P&BI sector appear to be possible.
Visualizing such a nightmare competitor would enable the Dutch P&BI to develop
effective business strategies, which should also take into account changing policy and
regulation, environmental awareness and future P&B products demand.
In this paper, a scenario analysis with the support of a quantitative model is applied
to underpin the process of business strategy and policy-making with respect to
investments/divestments in this industry. To this end, the process of combining scenario
analysis and System Dynamics modelling is addressed to explore and evaluate
production capacity changes in the Dutch P&BI subject to a variety of scenarios. The
relevant trends identified in a conceptual scenario analysis are translated into inputs for
a System Dynamics model and related therein to investment/divestment options since
the model also captures the technical essence of this industry.
1.1. Background and Expected Behaviour
Companies in the Dutch P&BI transform new, virgin pulp and recycled fibres into P&B
products (Berends, 2001; VNP 2002). Its level of vertical integration (Food and
Agriculture Organization, 1973) is limited, since the industry only produces a small
amount of mechanical pulp from wood and further transformation such as packaging or
newsprint products is limited.
The Dutch P&BI currently comprises 27 mills owned by 17 companies. Most of
these are managed from international headquarters where decisions about investments,
divestments and production quantities are taken. In 2002, the mills produced
approximately 3.3 million tons of final products (VNP, 2002). Those form the first link
in the P&B production chain in the Netherlands, where packaging material, graphic
paper and hygienic and sanitary paper is produced in order of volume. The greater part
of the production is exported, except for the last category that is produced mainly for
national consumption.
Since the 1980s, the Dutch P&BI has increased the use of recovered paper in its
production cycle. Nowadays, the basic raw material this industry uses consists of fibres
from recovered paper (75%), imported virgin wood pulp (21%) and home produced
pulp (4%) (VNP, 2002) (See figure 1).
Approximately 76% of the recovered paper is imported, mainly from Germany,
Belgium, the United Kingdom, France and the United States (VNP, 2002). The Dutch
recovered paper industry supplies the remaining 24%. Although this industry gathers
enough recovered paper to guarantee the Dutch P&BI’s demand, import of certain
recovered paper grades is required to meet the required basic output volume and quality
(Bouwens, 2004).
Due to its dependency on import, the Dutch P&BI must pay the international
market prices for wood and virgin pulp. The same holds for secondary, recycled fibres,
especially after the recent increase of oil and gas prices. In both cases, transportation
costs are incurred in addition to the fibres cost.
Investments in extra production capacity require large amounts of financial
resources, since this is a capital-intensive industry. The competitive advantage of state-
of-the art machinery investment on average last 3.75 years due to the ever increasing
size of machinery available and used (Berends, 2001).
The position in global and regional markets appears to limit the Dutch P&BI’s
adaptability and range of options in case new competitors enter their playing field or
unexpected changes in its environment occur.
Recovered Paper
75%) Export
Dutch Recovered Paper and Board
Paper Industry =e 7%) Export
zee
726 86% Board Industry 25% > 25%
Recovered Paper Dutch Paper ang
Import Board 7%—r| Disposal
18% Consumption
25%| Paper and Board
Import
Wood Pulp
3
Figure 1: Flow of volumes of the Dutch Paper and Board Industry (percentage mass)
AS an initial stepping-stone for initiating the discussion at industry level, this research is
meant to uncover the non-linear dynamics affecting new investments in the current
industry structure.
In general, this industry expects that several factors could produce in the near future
the stagnation or even the decline of the current increasing trend of sold products of the
Dutch P&BI. Some considered factors affecting this industry were the business climate
in the Netherlands, paper and board consumption, technical developments of production
machinery, social awareness for recycling, country’s welfare but especially an
enormous investment on paper and board production outside the current industry. The
expected behaviour of the sold products before and after the introduction of a new
facility for paper and board production appears in Figure 2.
Dutch P&BI Sold Tonnes
New facility
_starts
operations
0 5 10 15 20 25 30 Years
Figure 2: Dutch Paper and Board Industry's Sold Tonnes reference mode
The concem of this industry in the developments in future scenarios is reflected on
the gray area which portrays the different trends of the sold products depending on the
combination of environmental factors. This research also explores the performance of
the current industry in alternative future scenarios when investments are done outside
the current industry.
1.2. Objective, research question and outline
This paper aims at analyzing the impact on the Dutch P&BI's capacity utilisation, sales
and profitability of a new investment in a state-of-the-art facility for the production of
pulp and paper. The main research question is:
What are the economic consequences for the Dutch P&BI when a state-of-the-art,
competitive facility for the processing, production and transformation of primary
and/or secondary fibres is realized and competes with the Dutch P &BI?
To support the analysis and visualization of the effects of major, competitive
investments in such a mature industry, a System Dynamics model was developed and
implemented by determining the boundaries, important variables, major mechanisms
and performance indicators of the Dutch P&BI. From this model, the scenario-space
was expanded by identifying highly important and uncertain factors that drive the
system’s dynamics. The combination of this scenario-space and quantitative System
Dynamics model is expected to facilitate a systematic scenario analysis.
The modelling approach is presented in section 2. Section 3 addresses the model
and the model testing. Section 4 focuses on the scenario construction, the new facilities’
design and the scenarios’ outcomes. Finally, the conclusions and limitations of this
study are discussed in section 5.
2. Modelling approach
The Dutch P&BI is a complex system with dynamics that appear difficult to replicate in
a model. As a first step in the modelling process, system decomposition was explicitly
addressed (Dijkema et. al, 2003). A simplified model consisting of some relevant
domains was developed, which is expected to facilitate the understanding of this system
and its components and to learn about the system’s behaviour.
A suitable model type for the Dutch P&BI is a continuous one (Wu, 2000), because
it allows strategic decision-making, capacity planning and conceptual design and
because the information's aggregation level is high (Industry level), the study period is
long due to large investment cyclicality of this industry and the P&B production process
is continuous. It is possible to describe the Dutch P&BI as a structure that contains
(Roberts, 1978):
* Physical aspects: pulping, paper production and the use of recovered paper.
* Investment, price and cost policies that affect the decision-making process. These
include raw materials price, end product price and government regulations.
* Feedback loops, not only informational -sales for estimating the raw material need-,
but also physical - recycling of recovered paper -.
System Dynamics appears to be a suitable modelling method for this research. By
applying System Dynamics (Forrester, 1961), the principles and techniques of control
systems are applied in order to provide sufficient understanding of the strategic
processes involved.
The conceptual model was developed by using a systems analysis approach (Miser &
Quade, 1985) in order to identify factors under the influence of the Dutch P&BI and
those beyond its influence. The approach identifies:
= A problem owner: An actor with a feeling of unease about a situation - the Dutch
P&BI -, who sets the objectives, establishes the constraints for the solution-space
and decides which solution to implement.
= Relevant external factors affecting the system’s performance: The problem owner
cannot or can only partially determine the value of these factors.
= Instruments: the problem owner has direct influence and which will modify the
output of the system.
= Criteria: the problem owner can set a norm on these factors. Thereby, a system state
is evaluated, now or in the future, based on the problem owner s objectives.
The identification of relevant external factors driving the system is key to the model
development and further scenario analysis. Once identified, a reasonable number of
mega-trends determining these factors can he established. Mega-trends dramatically
affect the performance of the system, but the problem owner has no means to influence
them.
In the modelling process, a systematic combination of mega-trends will be the input
to a quantitative model of the Dutch P&BI. Any combination of mega-trend extremes
represents a scenario for which the simulation can be run to explore possible future
states and responses of the system.
The scenario analysis is meant to assist in the learning process of a system model in
the context of policy and/or system design (Schwartz, 1997). The intention of this
scenario analysis of the Dutch P&BI system’s model was to describe images of the
future in 20 years, which represents five consecutive investment cycles. This period
provided room to observe the evolution of the installed capacity, and consequently the
capital stock changes due to investments and divestments.
The quantitative model must be tested and evaluated for suitability and robustness
when analyzing the model output under different scenario. The software Powersim
Studio Academic 2003 was used for the simulation of the Dutch P&BI industry model.
3. The industry model development
In the previous section, a modelling approach has been introduced to enable the
definition of a quantitative model. To enable any analysis of the impact of investments
on the current Dutch P&BI, the simulation model must include elements that support
the analysis of production capacity changes. Not only the physical domain but also the
decision-domain should be represented in the model. More specifically, what are the
relevant conditions for an investment decision, what are the consequences of
investments in this industry regarding capacity, what happens when there is a situation
of an excess capacity in this industry and how are the funds for investments in this
industry generated.
To underpin the selection of the model boundaries and adequately support the
analysis of investment decisions in the Dutch P&BI, literature was reviewed to explore
the above-mentioned questions. Some recurrent issues regarding investment decisions at
different aggregation levels and between industries were recognized that support the
explanation and further analysis of the questions explored.
The following works were used to identify relevant causal relationships in the model.
Tremborg, Buongiomo, & Solberg (2000) present economics and production planning,
in the form of profitability and past production respectively, as the source for capacity
changes. The emphasis and focus on economics or production planning, however, varies
between authors. Mandal & Sohal (1998) base the capacity expansion on the increase of
average sales revenue and the desired capacity in order to comply with the demand.
Chowdhury & Sahu (1992) indicate that demand and a fraction of the total revenue are
causes for changes in production rate. Mohapatra, Bora, & Sahu (1984) use an available
fund -a reserve coming from profits after taxes- and a desired harvesting rate for
changing harvesting rates.
Unlike the above-mentioned works, the following authors analyze only the
production cycle, removing economics. Corben, Stevenson, & Wolstenholme (1999) see
the production potential and the efficiency of the production process as direct causes of
production rate changes. Minegishi & Thiel (2000) indicate that the gap between the
expected and the actual rate triggers changes in production rate. Lyneis (2000) indicates
an order backlog, which depends on the gap between projected demand and target
utilisation.
The following works focus only on economic resources, neglecting the production
cycle. Kantardgi (2003) sees that an enterprise fund for investments and the
effectiveness of funds use affect the production levels. Jan & Hsiao (2004) base the
improvement in manufacturing ability on increasing R&D investments.
The recurrent issues extracted from these sources are (1) the description of the
characteristic production function and (2) the physical flow of the industry under study
and how do these relate to (a) production capacity; (b) the changes in production
capacity based on utilisation of the installed capacity; (c) the investments and
divestments in relation to the utilisation of the installed capacity; and (d) the profits as a
source for investments.
/ %
Instruments
\ ey
Divestment
Domain
Material
Capacty wataass
Domain
(External)
\ Factors /
Mega-trends | \ criteria)
Investment
Domain
Dutch Paper and Board Industry System
Figure 3: Initial System Diagram
Based on the systems analysis approach (Miser & Quade, 1985), it is then possible
to decompose the industry model into different issues and relate each with a specific
domain in the model of the Dutch P&BI, as follows (See Figure 2):
= Investment domain: this domain deals with the conditions for an investment decision
and the evolution of such an investment in monetary terms.
= Capacity domain: this domain describes the changes in capacity due to investments
and divestments.
= Divestment domain: this domain deals with the conditions for a divestment decision
= Material Domain: this domain deals with the physical flow and production functions
of the Dutch P&BI
= Performance Domain: this domain deals with the results of the Dutch P&BI
These domains are interrelated. The modelling of each domain is described in the
following sections.
3.1. Investment domain
This domain deals with the conditions for an investment decision and its evolution in
monetary terms (See figure 3 for the causal diagram). A primary assumption is that
resources for investments in the current structure of the Dutch P&BI come from a
reserve of the generated profits. The total profits - or losses - of the Dutch P&BI are
obtained from the total profits per unit of output and the amount of P&B products sold
locally and internationally. In a situation of profits, a percentage of the total profits
make up a reserve for future investments in capacity of any of the three production
functions (wood pulp production, recycled fibres production and production of P&B). In
a situation of losses, the reserve will drain at the same proportion.
A money release from the reserve will take place under the following conditions:
= the reserve for investment surpasses a certain threshold, which secures the existence
of enough resources for any investment decision
= the expected capacity utilisation surpasses an upper limit, which is close to total
utilisation. This indicates likelihood of insufficient production capacity in the
future. The expected capacity utilisation is the comparison of the current production
rate in any production function and its expected capacity after adding the extra
capacity coming from the new investment.
= there growth in sales, which indicates possible increase of the expected capacity
utilisation
= the profits moving average is positive, which indicates possible future profits
The amount of money released from the Reserve for Investment is equal to the
Investment Requirement in each production function. In the implementation of the
model presented, the value for the production of wood pulp is based on the data of
Bergman & Johansson (2002), while for the recycled fibres production the value is
based on the data of the positioning paper of Zittema (2005). The value for the P&B
production is based on the data of Romme (1994).
The released money becomes an available budget for deploying the capacity
increase, which is consumed in a certain investment period and tums into capital stock.
The capital stock is subject to depreciation in a certain period.
4 Processing Pup "4 Processing Pulp
% Capial Stock % Depreciation
Investment Period Depreciation Period /
Reserve Threshold ~~
Investment Domain (For the Processing Pulp stream)
Figure 4: Investment Domain of the Dutch P&BI system
3.2. Capacity domain
This domain describes changes in production capacity due to investments and
divestments (See figure 4 for the causal diagram). A capacity increase happens when an
investment decision occurs and produces a money release from the Reserve for
Investments. This money release translates into an expected capacity increase of any of
the three production functions. Here, the expected capacity is the needed capacity level
that results from the addition of capacity to the previous expected capacity. The
translation from money to capacity depends on the Investment to Capacity Coefficient,
which relates the produced tonnes per year with invested Euros. In the model
implementation, this coefficient is assumed to be fixed and does not include the effect
of economy-of-scale (ABN AMRO, 2004).
The expected capacity is the target, which the current capacity will aim to achieve.
The current capacity expands to the expected capacity in a slower pace than the
investment decision due to the time elapsed between the request, the delivery and the
installation of the machinery and the training of the employees. These activities belong
to the investment period that precedes operation of additional capacity.
With the expansion of the current capacity, the labour force increases under the
assumption that new units are installed. The number new employees hired depends on
the current capacity expansion and a factor translating capacity into labour (ABN
AMRO, 2004). This indicates the required extra personnel per ton per year of extra
capacity.
A divestment decision triggers the opposite situation. Once a divestment decision
occurs, the current capacity of any of the three production functions reduces. This
reduction depends on the Current Capacity, the production rate and the Current
Capacity Threshold. The effect is an increase of the Current Capacity Utilisation above
the threshold. The current capacity reduction affects the expected capacity, reducing it
at the same pace and producing layoffs. The layoff magnitude has a direct relation with
the current capacity reduction and a factor translating capacity into labour. Once the
layoffs become effective, the number of employees reduces and the employees join a
compensation programme for a certain period. While staying in the programme, the
employees receive an annual compensation.
Capacity Domain (For the Processing Pulp stream)
Figure 5: Capacity Domain of the Dutch P&BI system
3.3. Divestment domain
This domain deals with the conditions for a divestment decision (See figure 5 for the
causal diagram). A divestment decision, and therefore a capacity reduction of the
recycling P&B and P&B manufacturing production function happens under the
following conditions:
= When the current capacity utilisation declines, surpassing a lower limit - current
capacity utilisation threshold -, in order to prevent a situation of excessive under
utilisation
= When there is a reduction from last year’s sales, which indicates possible negative
trend of the current capacity utilisation
Since the Dutch P&BI has the possibility to buy pulp for its P&B production the
condition of sales reduction is not necessary for the pulping pulpwood production
function.
PRB Sales charge /
Divestment Domain (Fort the Processing Pulp stream)
Figure 6: Divestment Domain of the Dutch P&BI system
3.4. Material Domain
This domain deals with the physical flow and production functions of the Dutch P&BI
(See figure 6 for the stock-and-flow diagram). The Dutch P&BI uses new and recycled
wood fibres for its production process. Based on the Raw Material Requirement, it
produces new wood fibres and purchases the required amount of new fibres and
recovered P&B for the production process. Changes in the P&B Sales Forecast will
or
soyeuliuo saiqy poom pepAdal Jo Junowe yueyodu uy ‘UoNDeT[00 gxq 10} wWaysAs
peztuefio ue aaey yey} seujunoo ut payehaiihe useq oaey asoy], ‘seuunod ubtar0j
Ul paleAodal G2yq Waly peonpod st sarqy poom pepaAoer ayy Jo ped ssyearh ayy,
woyshs [qd YOINC ay} Jo Urewog [eLayeW +, ambiy
urept wond Pu J
~
‘% Wood Pulp —sh
Production’ |
woos pup (1)
Requirement a
yao
‘Stocl]Recavered Paper
Popa
Foreign
weed ore
Recovered P&B
Oe
Dutch Paper and Board Industry
ilereaucton
current Reaycing Pas
PB Sales Forecast
Current Processing
Sipespecy™ — \,
a
—) f..
any Ror
NL Colected pas NtContribution
von Rate Recovered PAS
\owara MK |
imported PAB
[Paper and Board Converting Industry
mime =|)
umption |
Disposal Rate
c
Accumlation Perea
I. rape and oar consumption
piport NL Cotected|
PAB Recovered PAB
_) “or local demand
Mt Paper and Board Collection Industry
NL Average
consumption per
‘capita
la
tithe
O
Int Growth ingex
INL Consumption
NL Corgumtion
beaths
=)
NL Dedine Index
“Ayoedeo uotonpard a[qeyreae UALS oy} YIM UoTeTaL Joaltp e sey dnd poom peonpaid
jo JUNoWR at] ‘UoNIppe Uy ‘salqIy MoU 10} yUoWAIINbal ot JaA09 0} paseyaind 10/pue
peonpaid Aqyeoo] are salqy poom max ‘sjuatarmbar sauqy poyoAoes pue meu oy) efueyo
from P&B recovered in the Netherlands. The increasing P&B consumption makes
available more recovered P&B from both sources, which secures the supply of recycled
fibres to the Dutch P&B Industry.
New and recycled wood fibres are combined in a certain proportion. Changes in the
proportion of new and recycled wood fibres will affect the final mix to produce P&B
products.
Depending on the available capacity, recovered P&B is recycled and mixed with
new wood fibres to produce P&B products, which become part of the available stock for
local and intemational sales. Based on the P&B Consumption Forecast and the % P&B
for NL, this stock is used to satisfy local and international demand. The historical data
from the Confederation of European Paper Industry’ served as a basis for the evaluation
of the suitability of extrapolation as a method to obtain future values of Raw Material
Need, % Non-Fibrous Material, % Recovered Paper, % Wood Pulp Production, %
Waste, NL Average Consumption and Foreign Average Consumption.
End consumers utilize end P&B goods, which are transformed by the P&B
Conversion Industry into end P&B goods. The amount of P&B finally consumed
depends on the population and its per capita average consumption. The Paper and Board
Recovery Industry collects P&B products from households and businesses once the end
consumers have used and discarded them.
3.5. Performance domain
This domain deals with the results of the Dutch P&BI (See figure 7 for the causal
diagram). A basic assumption is that market-clearing mechanisms set the quantity of
products sold based on the price level. According to neoclassical economics theory this
mechanism also sets the industry profits (e.g. Mankiw (1998); Png (1998); Himmelweit,
Simonetti, & Trigg (2001)).
PEE
Recycling P&B
DP&BI Wood
Puip Production
Employees
Wood Pulp
Production
Depreciation
Processing Pulp
Depreciation
Recycling P&B.
Depreciation
Performance Domain
Figure 8: Performance Domain of the Dutch P&BI system
1 http://www.vnp-online.nl/index.cfm?firm=vnp&fuseaction=show.page&pageld=160
ig
According to Neoclassical Economics, total revenues and total costs determine total
profits. Total revenue is obtained from the sales of P&B products, both locally and
intemationally, while taking prices as given. From the sector research by ABN AMRO
(2004) it was possible to extract average costs per item produced.
The average cost relates to the purchase of pulpwood or woodchips, wood pulp and
recovered P&B. Annual Other Costs are indirect costs that relate to the P&B production
rate. Annual Energy Costs takes into account the energy use in each production
function. Annual Labour Costs relates to the number of employees in the Dutch P&BI
and their Average Annual Compensation. Annual Divestment Cost takes into account
the Persons in Compensation and the Average Annual Compensation. Annual
Maintenance Costs relates to the Current Capacity in each production function and
Annual Unitary Maintenance Costs, which increases with the ageing of the machinery.
Depreciation Cost in each production function comes from the Investment Domain.
3.6. Conceptual overview
The information of each domain, structured by means of causal loop diagrams, is
presented in a system diagram showing the relevant domains (See Figure 8).
While developing the description of each domain, external factors, instruments and
criteria were identified. External factors are beyond the control of the Dutch P&BI;
instruments are factors the Dutch P&BI has control over and criteria provide
information about the situation of the system.
Instruments
P&B Consumption Forecast 7 CaPasl to labou Costicint
Ageing of Expected Capaciy Investment
Threshold
= Investment Period
+ Depreciation Perioa
-
i External Factors
‘= Investment Requirement
Reserve for Investment
3 Reserve Threshold Divestment
Current Capacity Divestment Domain
ret
= Copaci 4) Domain
freonieat Gena Ot [4 Domain. |-——
Criteria
wma ‘© Current Capacity
aa Utiisaton
‘Current Capacity
Expected Capacity
Population
= Average Consumption per Capita IN © Disposal
© Improvement in Collection System ) © Ni Collected PAB
2 WCotected PAB or NL Export
2 %Recovered PAB { 2 3 I Waste
2 Sood Pup Production Am Ze i Drael NSees
2 New Factty Recovered PAB \P investment 2 DARE Export Sates
Requirement sy TBehen
+ New Fact Wood Pup Sales DRAB! Total Profits
New Facity Recycled bres Sales
+ New Facility NL Sales ce“ Gapieleter }
& rial Cost Dutch Paper and Board Industry System NS /
\ J
Figure 9: Performance Domain of the Dutch P&BI system
This conceptual model is transformed into a quantitative representation” by establishing
the corresponding equations that reflect relations between variables using System
Dynamics symbols.
2 The complete model is available at http://www.tbm.tudelft.nl/live/binaries/e857ec2b-ca87-4360-aa70-
d8a068d6bba7/doc/CM.ChiongMeza.pdf
12
3.7. Model testing
The list elaborated by Barlas (1996) served as a starting point for the selection of tests
supporting the validation of the Dutch P&BI system’s model. The final application of a
test depends on the data availability from the real system.
Barlas (1996) present three groups of test. The first group named ‘Direct structure
tests’ focus on the relations in the model by comparing it with the knowledge of the real
system, without running the simulation model. The second group called ‘Structure-
oriented behaviour tests’ runs the model to study the structure of the model indirectly.
The third group, appointed as ‘Behaviour pattern tests’, assesses the trends of the model
output based on the data of the real system.
From the ‘Direct structure tests’, the following were conducted: theoretical
structure and parameter confirmation, direct extreme conditions, empirical structure
confirmation, empirical parameter confirmation and face validation with some members
of the Knowledge Centre Paper and Board.
From the ‘Structure-oriented behaviour tests’, the following were conducted:
extreme conditions and behaviour sensitivity analysis.
To observe the behaviour pattern, Theil inequality statistics (Sterman, 1984),
provided a measure of proximity between the model output and the real system data
based on the Mean Square Error. Figure 9 presents an example of the measure of Theil
inequality for the P&B Sales.
Year | P&BSales(M) | P&B Sales (HD) Theil Inequality for P&B Sales
1991 2798438 2862000
1992 2817911 2833000 3800000
3700000
1993 2857551 2857000 i 3500000
3300000
1994 2916186 3011000 | | © 3100000 ———e
2200000
1995 2971922 2968000 2700000
1996 3012042 3000000 ey mp ne ep a eam
1997 3050540 3162000 aA aa AR aA RRR OR
1998 3125158 3180000 | | [——*S® Sales on Year
P&B Sales (HD)
1999 3250085 3255000
2000 3380537 3332000
2001 3482670 3174000
2002 3571674 3338000
2003 3670262 3341000 U™ =0.09 US = 0.52 US =0.39
Figure 10: Theil inequality statistics for P&B Sales
The Mean Square Error is composed by the difference in averages, variances and
covariance. The average difference (U™) represents a constant shift of the model data in
relation to the historical data. The variance difference (U‘) represents different
amplitudes in fluctuation of the model data in relation to the historical data. The
covariance difference (U°) represents a point-by-point difference of the model data in
relation to the historical data. In this example, the model output mainly differs in
amplitude and point-by-point accuracy from the historical data.
After performing the selected tests, the results provided sufficient confidence on the
model structure.
13
4. Scenario analysis
Once the Dutch P&BI system’s model has been established and tested for suitability, it
is exposed to different scenarios in order to observe its behaviour in possible futures.
4.1. Scenario C onstruction
The systematic plan of Schwartz (1997) for designing environmental scenarios has
served as a guideline. The purpose is to identify mega trends and arrange them in a way
that they span the scenario space. The criteria for selecting mega trends are to choose
those with high importance regarding the effect on the policy objectives and with high
uncertainty in future developments (Schwartz, 1997). After making a preliminary list of
relevant trends and evaluating them following the definition of mega trends, the ones
that met these criteria were:
¢ Demand-shift for P&B products: its importance is high because it affects the future
P&B production; its development is uncertain because of the availability of
competitive substitute products and technologies
¢ Social awareness for the use of recycled material: its importance is high because it
affects the mix of fibres in the production of P&B; its impact is uncertain because
the availability of recovered P&B appears to depend increasingly on the volatile
evolution of fuel prices, as recovered P&B is a source of energy.
¢ Dutch business environment: the importance is high because it depends on the
different goverment coalitions in each administration period, which in tum
influences the decisions taken at international headquarters related to the continuity
of Dutch mills. These decisions are also uncertain because of the factors that are
considered in addition to good performance.
Regarding the demand-shift for P&B products, one extreme represents an intensive use
of paper while the other extreme is massive P&B substitution. Concerning the social
awareness of the use of recycled material, on the one end of the scale there is a tendency
to use only recycled wood fibres, on the other end a preference for virgin wood fibres.
About the Dutch business environment, one extreme represents a supportive business
environment; the other extreme would represent a discouraging business environment.
Initially, each combination of the mega-trend extremes produces a possible image of the
future (See Table1). Analysis of some of these combinations does not require urgent
simulation. This is the case for combinations six and eight of table 1: In a situation of
declining demand-shift for P&B products and a discouraging business environment, no
matter the social awareness of recycled material, future investments on capacity
expansion are not attractive given the adverse atmosphere. The other combinations of
mega trends, however, do require simulation for suitable analyses using the System
Dynamics model, because the system’s behaviour is hard to predict. This is the case for
combinations one to five and seven of Table 1.
In each combination, the mega trend of social awareness of recycled material
supports the choice of a new facility’s set-up for the scenario analysis from the five
configurations that are presented in section 4.2. When the trend points toward recycled
material, the set-ups dealing with this input become suitable for testing. The set-ups
14
using new wood fibres become suitable for testing when the trend points toward new
wood fibres.
Additionally, the level of demand-shift for P&B products helps to determine the
production capacity of each set-up (See section 4.2).
Table 1: Combination of mega trends and related environmental scenarios’ name
Combination | Demand-shift | Social awareness Dutch
of Mega for P&B of recycled business Environmental Scenario
trends products material environment
1 Intensive use Recycled fibres Supportive ® Endless sustainable paper
2 Intensive use Recycled fibres Discouraging g€ Poor environmental industry
3 Intensive use New wood fibres Supportive S2) Endless woody paper
4 Intensive use New wood fibres Discouraging 2 Poor woody industry
5 Substitution Recycled fibres Supportive 2 Autumn of sustainable paper
6 Substitution Recycled fibres Discouraging a Decay of the paper age
7 Substitution New wood fibres Supportive os Autumn of woody paper
8 Substitution New wood fibres | Discouraging a Decay of the paper age
Once the outline of each scenario is completed, a description of how mega trends
create a possible future for the Dutch P&BI is developed. Following the order of table 1,
the worldview of each combination is described:
® Endless sustainable paper: The demand-shift for P&B products grows because
there is little P&B substitution with other materials and technologies; this demand
increase means more P&B products consumption and therefore more P&B
recovery. The P&B production includes more recycled fibres in their process as
there is more social awareness regarding recycled material use; this comes with the
increasing P&B consumption. A supportive business environment provides
favourable conditions, which gives a final impulse for new investments by external
parties on large capacities using recycled fibres in their production processes.
Poor environmental industry: Here the demand-shift for P&B products also grows
because there is little P&B substitution with other materials and technologies; this
increase in demand means more P&B products consumption and therefore more
P&B recovery. The P&B production includes more recycled fibres in their process
since there is more social consciousness about recycled material use; this comes
with the increasing P&B consumption. However, a discouraging business
environment provides unfavourable conditions, which reduces the chances for new
investments focused on large capacities but may still be attractive for investments
directed to smaller capacities processing recycled fibres.
@ Endless woody paper: This worldview is similar to the endless sustainable paper.
The difference is the little social awareness for the environment and therefore for
15
the recovered P&B use in the production process. Here, new investments focus on
large capacities transforming pulpwood into new wood fibres.
w Poor woody industry: The demand-shift for P&B products grows because there is
little P&B substitution with other materials and technologies; this increase in
demand means more consumption of P&B products and therefore more P&B
recovery. However, there is little social awareness for the environment and
therefore for the recovered P&B reuse in the production process. At the same time,
a discouraging business environment provides unfavourable conditions, which
reduces the chances for new investments oriented to large capacities. However, it is
still attractive to invest in smaller capacities that transform pulpwood into new
wood fibres.
Autumn of sustainable paper: The demand-shift for P&B products declines due to
the P&B substitution with other materials and technologies. This decrease in
demand means less consumption of P&B products and therefore less P&B
recovering. However, there is social awareness for the environment and therefore
for the recovered P&B use in the production process. Simultaneously, a supportive
business environment provides favourable conditions, creating incentives for new
investments at a small scale with the focus on processing recycled fibres.
2% Autumn of woody paper: This worldview is similar to the autumn of sustainable
paper. The difference is the little social awareness for the environment and
therefore for the recovered P&B use in the production process. Here, new
investments focus on small capacities transforming pulpwood into new wood
fibres.
4.2. Scenario implementation
Conceming the mega trends, the related factors that will be inputs to the System
Dynamics model should adapt to match the scenario description.
When dealing with the demand-shift for P&B products, the average consumption
per capita will increase in a situation of intensive use and it will decrease in a situation
of substitution.
When the mega trend of social awareness of recycled material tends to more
recycled fibres use, the improvement in collection system (i.e. % Collection NL, %
collected P&B for NL, % recovered P&B) will increase, while % wood pulp production
and annual average raw material cost will decrease. When the mega trend of social
awareness of recycled material tends to more new wood fibres use, the opposite will
occur.
When dealing with a supportive Dutch business environment, the % reserve for
investment will increase while the reserve threshold and the current capacity divestment
threshold will decrease. In the situation of a discouraging Dutch business environment,
the opposite will occur. Appendix 1 presents the input values of the external factors
regarding the mega trends.
4.3. New Facility
The effect of an investment from outside the current Dutch P&BI is analysed by adding
a new facility for pulp and/or paper production that competes with the Dutch P&BI in
national and international sales. The Dutch P&BI deals with this new facility as an
extemal factor, which means that it cannot exert influence on the new facility, but the
16
new facility will affect the dynamics of the Dutch P&BI.
The emergence of a new facility provides new insights about the Dutch P&BI’s
continuity, because any investment out of the industry’s current structure could mean
less improvement in the current production functions’ capacity and stagnation of its
capital stock. This new facility will basically affect the raw materials supply to the
Dutch P&BI and the P&B products supply to the market, triggering changes that would
affect the behaviour of the Dutch P&BI system’s domains.
The set-ups for the new facility considered are a wood pulp plant, a recycled fibres
plant, a P&B plant using wood pulp, a P&B plant using recycled fibres and a P&B plant
using wood pulp and recycled fibres. Both set-ups are based on the production functions
of the Dutch P&BI: wood pulp production, P&B production and recycled fibres
production. The relevant domains for the new facility's design are the investment, the
depreciation of the capital stock, the installation of the capacity, the performance (in
terms of profits or losses generated by the new facility) and the production function(s).
It is assumed that the new facility will provide P&B products to the market at
competitive prices; thereby covering part of the Dutch P&BI forecasted demand and
therefore reducing its sales. The new facility for producing P&B products with mixed
fibres will follow the same trends of the Dutch P&BI regarding raw material purchase,
raw materials proportions, waste production and P&B price volatility.
The P&B demand in each environmental scenario will help to determine the
capacity for each set-up in each combination (See reference values in Appendix 2).
These values become the medium capacity (MC) for the final production function or the
only production function in the new facility’s set-up. An increase and decrease in 50%
of the medium capacity become the small capacity (SC) and the large capacity (LC)
respectively (See transformed capacities in relation with the environmental scenario in
Appendix 3). Since little information about P&B machinery cost is available, the
gathered information for each production function was adapted from the average values
by means of the formula for the calculation of investment costs by regression:
1) (cy
c.
In the formula, I, and I represent the original and the new investment costs; C, and
C represent the original and the new plant capacity, and a is the regression exponent. It
is possible to reduce unitary costs in dedicated plants, i.e. plants optimally adapted to a
process or product (Rauch & Plooy, 2003). However, when a plant produces small
quantities, the capital costs of such a plant become very important since it heads
oppositely to the variable costs. In the introduced formula, « provides the influence
magnitude of the capital cost at different capacities. The a values for most plants and
equipments are normally around 0.6 or 0.7 (Humphreys & Wellman, 1996) while the
average is typically 0.65 (Gerrard, 2000). This average was used for estimating different
capacities of each production function, because the equipment inventory of Humphrey
and Wellman only has a general approximation to the paper production process
equipment.
The different capacities and the corresponding investment budgets in relation to the
defined scenarios based on the values of Appendix 2 and the formula for the calculation
of investment costs by regression were obtained as follows. For new facilities with two
or three production functions, the final production function (P&B production)
17
determines the capacity of the previous production function (recycling P&B and / or
pulping pulpwood) depending on the waste proportion (5% for P&B production, 30%
for recycling and 25% for pulping). Additionally, the recycled fibres proportion when
producing P&B also affects the previous production function capacity in the case of a
facility with three production functions. Afterwards, the formula for the calculation of
investment costs by regression supports the transformation of the investment budgets
from the calculated production (See the adjusted capacities in A ppendix 4).
Each relevant set-up of the new facility will run independently from other set-ups in
each scenario in order to observe the individual performance and make comparisons of
the outcomes.
Once the input data is established for each scenario and facility, it is possible to run the
simulation model to analyse the Dutch P&BI system model’s dynamics.
4.4, Scenario results
The following section presents the results of the scenarios related to new facilities
producing and/or processing recycled fibres. These results relate to the scenarios of new
facilities producing and/or processing new wood fibres. The objective is to compare the
outcomes of the same criteria in different scenarios with different new facilities and
identify the best and the worst case for the Dutch P&BI.
* Results of Scenarios related to Recycled Fibres
The current capacity utilisation of the Dutch P&BI processing pulp production function
continues to grow in the three scenarios with different new facilities’ capacities using
recycled fibres in its production process (See Figure 10.a). The smallest growth belongs
to the scenario “autumn of the sustainable paper” in which the average consumption
decreases due to the use of P&B substitutes. An extreme decline of the P&B
consumption decreases the current capacity utilisation of the producing pulp production
function and a new facility even with the small capacity affects this utilisation (Scen5
P&B, Scen5 P&B Rec and Scend Rec). The largest growth belongs to the scenario
“poor environmental industry” where the Dutch business environment is discouraging.
In this scenario, the medium capacity of the new recycling facility in the environment
(Scen2 Rec) leaves more market to the Dutch P&BI.
In almost all cases, the expected capacity and the current capacity expands (See
Figure 10.b and c). The earliest capacity expansion is in 2009 and corresponds to the
facility producing recycled fibres in the scenario “endless sustainable paper”. The
exception is the facility producing P&B with only recycled fibres in the scenario
“autumn of the sustainable paper” (ScenS P&B Rec). The intervals between capacity
expansions are larger than 4 years. An unexpected result is that the facility producing
Recycled Fibres and the one producing P&B in this scenario only slow down the
increase of the current capacity utilisation of the Dutch P&BI processing pulp
production function but finally it reaches the same level achieved in the scenario with a
recycling facility. It is worth mentioning that the inverse picks in the graph correspond
to the moment when the new facilities for P&B production start operations due to the
initial calculation of the sales rate.
For the recycling current capacity utilisation, the simulations show that it reaches a
stable behaviour after 1999 with some variations after 2010, when the new facilities
start operations (See Figure 10.d). The exception corresponds to the new facility, which
18
only transforms recovered P&B into fibres at medium capacity, becoming the best
current capacity utilisation of this production function.
Figure 11: Dutch P&BI capacity related outputs when new facilities recycle P&B
Dutch P&BI Processing Pulp Current Capacity
Utilisation
ie Pe
“EEEEELGEEESREEEES
ERRERRR ERR S Ra
Year
Dutch P&BI Processing Pulp Expected Capacity
000 L=
Tonnes
(a)
(b)
Dutch P&BI Processing Pulp Current Capacity
oo —
Proportion
Dutch P&BI Wood Pulp Current Capacity
F sane
as
(d)
Dutch P&BI Recycling Current Capacity
Bonn a mite oo en
2 | secre | | se sr
(e)
Dutch P&BI Wood Pulp Current Capacity Utilisation
| “8 [camer ee
Be © sora
sof BESRERSREERERERS . :
Year
(g) (h)
egend:
Scen1 P&B: Scenario 1 with a mixed fibres P&B facility
Scen1 P&B Rec: Scenario 1 with a recycled fibres P&B facility
Scenl Rec: Scenario 1 with a recycled fibres facility
Scen2 P&B: Scenario 2 with a mixed fibres P&B facility
Scen2 P&B Rec: Scenario 2 with a recycled fibres P&B facility
Scen? Rec: Scenario 2 with a recycled fibres facility
Scen5 P&B: Scenario 5 with a mixed fibres P&B facility
Scen5 P&B Rec: Scenario 5 with a recycled fibres P&B facility
ScenS Rec: Scenario 5 with a recycled fibres facility
These capacity utilisations occur together with expansion of expected and current
capacity in all scenarios (See Figure 9.e and f). The earliest one starts in 1999 and
19
corresponds to the facility producing recycled fibres in the scenario “autumn of the
sustainable paper”.
The current capacity utilisation of the wood pulp production function is null in the
simulations because these scenarios emphasized the use of recovered P&B (See Figure
10.g). No increments in the expected capacity or the current capacity occur (See Figure
10.h and i).
Figure 12: Dutch P&BI sales, profits and capital stock output when new facilities recycle P&B
Dutch P&BI NL Sales Dutch P&BI Profits
B rss
2000000
Dutch P&BI Processing Pulp Capital Stock
& seomosceo
F seoaocena
Scen1 P&B: Scenario 1 with a mixed fibres P&B facility
Scen1 P&B Rec: Scenario 1 with a recycled fibres P&B facility
Scenl Rec: Scenario 1 with a recycled fibres facility
Scen2 P&B: Scenario 2 with a mixed fibres P&B facility
Scen2 P&B Rec: Scenario 2 with a recycled fibres P&B facility
Scen? Rec: Scenario 2 with a recycled fibres facility
Scen5 P&B: Scenario 5 with a mixed fibres P&B facility
os Scen5 P&B Rec: Scenario 5 with a recycled fibres P&B facility
eoetiane Scen5 Rec: Scenario 5 with a recycled fibres facility
hy [scans nee
F scaooa
The P&B NL Sales of the Dutch P&BI continues to grow, with some inverse picks
when the new facilities producing P&B start operations (See Figure 11.a). The best
situation is when the new facility recycles fibres in the “poor environmental industry”
scenario (Scen2 Rec) and the worst corresponds to the new facility producing P&B with
only recycled fibres in the “autumn of sustainable paper” scenario (Scen5 P&B Rec).
In general, the Dutch P&BI’s results grow following the fluctuation patterns
identified in the historical data of the sales, which is embedded in the simulation model
(See Figure 11.b). The best growth comes in the “poor environmental industry” scenario
when the new facility recycles fibres (Scen2 Rec) and the worst happens in the “autumn
of sustainable paper” scenario with the new facility recycles fibres (Scen5 Rec).
The capital stock in each production function behaves according to the expected
capacity expansion (See Figure 11.c, d and e). For processing pulp, the change in capital
stock occurs in 2009 and corresponds to the scenario “endless sustainable paper’ with
the facility producing recycled fibres. For the recycling production function, the earliest
change starts in 1999 and corresponds to the scenario “autumn of the sustainable paper”
20
with the facility producing recycled fibres. The wood pulp production function shows
no changes, which coincides with no changes in the expected capacity.
* Results of Scenarios related to New Wood Fibres
The current capacity utilisation of the processing pulp production function starts
growing but tends to stabilize in the last third of the simulation period in the three
scenarios with different new facilities’ capacities that use new wood fibres in its
production process (See Figure 12.a). The smallest growth belongs to the scenario
“autumn of the woody paper” in which the average consumption decreases due to the
use of substitutes of P&B. An extreme reduction of the P&B consumption decreases the
current capacity utilisation of the producing pulp production function and even a new
facility with the small capacity affects this utilisation (Scen7 New, Scen7 P&B New and
Scen7 P&B). The largest growth belongs to two scenarios: the “endless woody paper”
and the “poor woody industry” where the P&B average consumption increases but the
Dutch business environment is supportive in the former and discouraging in the latter.
In the “poor woody industry” scenario, the medium capacity of the new facility
producing new wood fibres leaves more market to the Dutch P&BI, allowing a faster
growth of the current capacity utilisation.
When there is P&B production with only new wood fibres, the growth is less steep
but reaches the same level at the end of the simulation period. In the “endless woody
paper”, the growth is slightly less steep than in the previous situation but also reaches
the same level at the end of the simulation period. In these scenarios, the increasing
average consumption compensates the competition for the market share.
For the recycling current capacity utilisation, the simulations show a continuous
growth (See Figure 12.d). Similar to the processing pulp current capacity utilisation, the
smallest growth belongs to the scenario “autumn of the woody paper” while the largest
growth belongs to the “endless woody paper” and the “poor woody industry” with the
same type of new facility’s set-ups in each scenario.
The current capacity utilisation of the wood pulp production function is one in all
the simulations because these scenarios emphasized the use of new wood pulp for the
P&B production (See Figure 12.g). The above-mentioned levels of capacity utilisation
occurred without an expansion of the expected production capacity in any production
function (See Figure 12.b, e and h). Consistently, the current capacity of each
production function remains the same (See Figure 12.c, f and i).
The NL Sales of P&B produced by the Dutch P&BI continues to grow only in the “poor
woody industry” with a new wood pulp set-up. In other cases, there is a slight decrease
in the previous trend before a new growth, e.g. Scen3 P&B and Scen4 P&B, or there is
trend toward a steady state, e.g. Scen7 P&B New and Scen7 P&B (See Figure 13.a).
In general, the results of the Dutch P&BI grow following the fluctuation patterns
identified in the historical data of the sales, which is embedded in the simulation model
(See Figure 13.b). The best growth comes in the “poor woody industry” scenario when
the new facility produces new wood pulp (Scen4 New) and the worst corresponds to the
“autumn of woody paper” scenario with the new facility producing P&B (Scen7 P&B).
21
Figure 13: Dutch P&BI capacity related output when new facilities produce new wood pulp
Dutch P&BI Processing Pulp Current Capacity
Dutch P&BI Processing Pulp Expected Capacity
Utilisation
ie AE see | Es =
o i scot New 2000000 =
serail SUSERR RRR RSET R AR [=
Year Scent Year —
(a) (b)
Dutch P&BI Processing Pulp Current Capacity Dutch P&BI Recycling Current Capacity Utilisation
& 200000 | “sezepcen
(o) (d)
Dutch P&BI Recycling Expected Capacity Dutch P&BI Recycling Current Capacity
boss = 2 ae
eaes sei foe
@ ©
Dutch P&BI Wood Pulp Current Capacity Utilisation Dutch P&BI Wood Pulp Expected Capacity
ges
i
(g)
Dutch P&BI Wood Pulp Current Capacity
Tonnes
Legend:
‘Scen3 New: Scenario 3 with a new wood fibres facility
Scen3 P&B New: Scenario 3 with a new wood fibres P&B facility
Scen3 P&B: Scenario 3 with a mixed fibres P&B facility
Scen4 New: Scenario 4 with a new wood fibres facility
Scen4 P&B New: Scenario 4 with a new wood fibres P&B facility
Scen4 P&B: Scenario 4 with a mixed fibres P&B facility
Scen7 New: Scenario 7 with a new wood fibres facility
Scen? P&B New: Scenario 7 with a new wood fibres P&B facility
Scen7 P&B: Scenario 7 with a mixed fibres P&B facility
The capital stock in each production function behaves according to the behaviour of the
expected capacity (See Figure 13.c, d and e). Since there was no expansion of the
capacity of any production function, the capital stock continues to decrease in time.
22
Figure 14: Dutch P&BI sales, profits and capital stock output when new facilities produce new wood
pulp
Dutch P&BI NL Sales Dutch P&BI Profits
po
(@) (b)
Dutch P&BI Processing Pulp Capital Stock Dutch P&BI Recycling Capital Stock
() (a)
Legend:
* — Scen3 New: Scenario 3 with a new wood fibres facility
Scen3 P&B New: Scenario 3 with a new wood fibres P&B facility
Scen3 P&B: Scenario 3 with a mixed fibres P&B facility
‘Scen4 New: Scenario 4 with a new wood fibres facility
‘Scen4 P&B New: Scenario 4 with a new wood fibres P&B facility
‘Scen4 P&B: Scenario 4 with a mixed fibres P&B facility
‘Scen? New: Scenario 7 with a new wood fibres facility
Scen? P&B New: Scenario 7 with a new wood fibres P&B facility
‘Scen? P&B: Scenario 7 with a mixed fibres P&B facility
Dutch P&BI Wood Pulp Capital Stock
Euros
5. Discussion and conclusion
The main research question focused on the impact of a nightmare competitor on the
current Dutch P&BI under different circumstances. The combination of three mega
trends that influence the Dutch P&BI system’s external factors produced six scenarios,
which were combined with five alternative set-ups of a new facility competing with the
existing industry. A System Dynamics model was developed and the scenarios were
used as input to the developed model. Simultaneously, the combination of scenario
analysis and System Dynamics was observed.
Regarding the scenarios related to recycled fibres, the best scenario for the Dutch P&BI
is the “poor environmental industry” while the new facility produces P&B using
recycled fibres only. In this scenario, the current capacity utilisation of the pulp
processing and recycling production functions grow as well as the sales and the profits.
The worst scenario results occur in the “autumn of the sustainable paper’, while
interacting with a new facility using recycled fibres. Here, three criteria show the lowest
performance, i.e. the current capacity utilisation, the national sales and the profits.
Regarding the scenarios related to virgin wood fibres, the best scenarios for the
Dutch P&BI are the “endless woody paper” and the “poor woody industry” scenario,
while interacting with a new facility using new wood fibres. Here, the current capacity
utilisation of the processing pulp and recycling production functions grow as well as the
23
sales and the profits. The worst case results occur in the “autumn of the sustainable
paper’, while interacting with a new facility that produces P&B with mixed fibres.
Therein, five criteria show the lowest performance, i.e. the current capacity utilisation,
the national sales and the profits. The low performance during low P&B demand while
competing with a new wood fibres facility may reflect the efficient process of the new
entrant, which reduces the sales of the incumbent industry.
A common result in both groups of scenarios is the dominating role of the Demand-
shift for P&B products. The Dutch P&BI achieves high values when this mega trend
points to the growing side while it performs low when this mega trend points to the
decreasing side. Moreover, the Social Awareness for recycling P&B supports the
achievement of high values since recycled paper prices are lower than new wood fibres.
Additionally, the Supporting business environment seems to have little effect to
compensate a decreasing P&B demand.
The Dutch P&BI currently has a restricted decision-making power since the main
decisions about investments, divestments and production quantities are made at
international headquarters, which limits their range of means to take action. With this
restricted decision-making power, the Dutch P&BI should focus on the optimization of
their current production processes, the efficient use of resources and the recycling of
produced waste in order to reduce the current cost structure of the production process.
While this cost reduction results in a more competitive Dutch P&BI and appreciation by
the international headquarters, it remains to be seen whether cost reduction will also win
new investments for the Dutch P&BI.
The execution of this research project involved the analysis of Dutch P&BI
production capacities interacting with different facilities in different scenarios. The
construction of the Dutch P&BI model supported the identification of possible
necessary changes of its own capacity in order to cope with changes in demand, use of
raw material and Dutch business environment. When dealing with capacity expansions,
the model supports the visualization of the future profits that this expansion may
provide. The Dutch P&BI should concentrate on achieving economically feasible and
sustainable capacity changes by persuading the international headquarters with the
support of this new evaluation tool.
Conceming the combination of Scenario Analysis and System Dynamics, the result was
a simulation model suitable for exploring the system’s behaviour in the present and
future based on certain assumptions while providing general figures of some
performance indicators.
The systematic plan of Schwartz (1997) for designing environmental scenarios was
enhanced by the quantitative approach of System Dynamics modelling and vice versa.
The design of the Dutch P&BI’s model by means of System Dynamics and the
delineation of the model boundaries using the systems approach (Miser & Quade, 1985)
assisted the process of identifying factors outside the scope of the problem owner. A
further analysis of those factors conceming their importance and uncertainty in relation
to the Dutch P&BI’s system facilitated the identification of mega-trends for expanding
the scenario space. The basic scenario analysis and the quantitative model supported the
methodical definition of the quantitative characteristics of each scenario and the type of
new facilities involved, which facilitated the study of evolutionary patterns resulting
from the interaction of the Dutch P&BI in different scenarios with new facilities.
24
The answers of the research questions as well as the recommendations must be
understood while taking into account the limitations of this research project during its
execution. Several choices were made in order to achieve balance between academic
demands and business needs, aggregation level and availability of information, technical
limitations of continuous models and project management. These choices obviously had
a repercussion in the model design.
One repercussion is that the Dutch P&BI model does not include all the features of
the real system. For example, the model does not include the evaluation of the elapsed
investment period to prevent a new expansion in production capacity in the Dutch P&BI
in the same period, which is on average 3.7 years. During the model testing, some
capacity expansion investments on the processing pulp and recycling production
functions did take place before that. In reality, carrying out another investment while the
previous one is currently deployed would be difficult since new machinery installation
is a long process; however, this may reflect a possible situation in which the Dutch
P&BI must quickly adjust to an increasing demand.
Another topic is the testing of the developed model. While national level
information was used for the construction of the model, European level information was
used for the validation though it is possible that the latter is a compilation of country
level information. The need for independent sources of information for validation
purposes is still necessary.
The purpose of modelling the Dutch P&BI and its interaction with a new facility was to
design an abstract and simplified view of some relevant domains in order to facilitate
the understanding of production capacity changes because of investment and divestment
and learn about the behaviour of the system in the present and in the future based on
certain assumptions. The simplification of the real system implies the exclusion of
several variables, such as policies for recruitment of human resources or policies for
merchandising, or the reduction of variables, such as the variation of energy prices and
fibres prices. This simplification helped to focus on those elements that contribute more
to the analysis based on a set of assumptions. This model therefore does not fully
represent the complete Dutch P&BI but only the parts relevant in the research project
executed.
As a follow-up study, the declining scenarios that were not included in this research
could be further analysed in order to observe the industry dynamics and identify levers
for managing this industry in an unfavourable scenario.
6. Acknowledgement
The authors thank Drs. Ing. A. Hooimeijer (Royal Dutch Paper and Board Association)
for sharing his knowledge of the Dutch Paper and Board Industry, bringing the business
perspective to this research project and providing access to the Competence Centre
Paper and Board.
7. References
ABN AMRO (2004, September). Factsheet. Retrieved on January 28th, 2005, from
http://www.abnamro.nl/nl/images/I_Papier_en_karton.pdf
25
Barlas, Y. (1996) Formal aspects of model validity and validation in system dynamics.
System Dynamics Review, Vol. 12, No. 3, Pp. 183 - 210.
Berends, P.A.J. (2001) Swinging industries: cycles, adjustment and performance: an
empirical examination of the international pulp and paper industry (Doctoral
dissertation, University of Maastricht, 2001). Maastricht: Universitaire Pers
Maastricht.
Bergman, M.A.; Johansson, P. (2002). Large investments in the pulp and paper
industry: a count data regression analysis [Electronic version]. Journal of Forest
Economics, Vol. 8, No. 1, Pp. 29 -52.
Bouwens, Bram (2004) Op papier gesteld: de geschiedenis van de Nederlandse papier-
en kartonindustrie in de twintigste eeuw. Utrecht: Boom. Pp. 307
Chowdhury, S.; Sahu, K.C. (1992) A System Dynamics Model for the Indian Oil and
Gas Exploration / Exploitation Industry [Electronic Version]. Technological
Forecasting and Social Change, Vol. 42, No. 1, Pp. 63-83.
Corben, D.; Stevenson, R.; Wolstenholme, E.F. (1999) Holistic oil field value
management: using system dynamics for ‘intermediate level' and ‘value-based'
modelling in the oil industry [Electronic Version]. Journal of the Operational
Research Society, Vol. 50, No. 4, 383-391.
Coyle, R.G. (1996) System Dynamics Modelling: A practical approach. London,
Chapman and Hall. Pp. 4, 20, 96 - 98, 109, 153 - 155.
Dijkema, G. P. J., Grievink, J. and Weijnen, M.P.C. (2003). Functional Modelling for a
Sustainable Petrochemical Industry. Transactions of the Institution of Chemical
Engineers Part B: Process Safety and Environmental Protection 81(5): 331-340.
Food and Agriculture Organization (1973) Guide For Planning Pulp And Paper
Enterprises. Rome: without publisher.
Forrester, J.W. (1961) Industrial Dynamics. Cambridge: The M.LT. Press. Pp. 13-18,
64-72.
Gerrard, A. M. (2000). Guide to capital cost estimating (4th edition ed.). Rugby:
Institution of Chemical Engineers.
Himmelweit, S.; Simonetti, R.; Trigg, A. (2001) Microeconomics : neoclassical and
institutional perspectives on economic behaviour. London: Thomson Learning. Pp.
208-209.
Humphreys, K.K.; Wellman, P. (1996) Basic Cost Engineering. New York: Marcel
Dekker Inc. Pp. 8 - 9.
Jan, T.-S.; Hsiao, C.-T. (2004, November) A four-role model of the automotive industry
development in developing countries: a case in Taiwan [Electronic version].
Journal of the Operational Research Society, Vol. 55, No. 11, Pp. 1145-1155.
Kantardgi, I. (2003) Dynamic Modelling of Environment-Industry Systems [Electronic
version]. Computational Science - ICCS, PT II, Pp. 188-194.
Lyneis, J.M. (2000, spring) System dynamics for market forecasting and structural
analysis [Electronic version]. System Dynamics Review, Vol. 16, No. 1, Pp. 3-25.
Mandal, P.; Sohal, A.S. (1998, January/February) Modeling Helps in Understanding
Policy Altematives: A Case (Peer-Reviewed Paper) [Electronic Version]. Journal
of Management in Engineering, Vol. 14, No. 1, Pp. 41-48.
Mankiw, N.G. ( 1998) Principles of Economics. Fort Worth: The Dryden Press. Pp. 59-
110.
Minegishi, S.; Thiel, D. (2000) System dynamics modeling and simulation of a
particular food supply chain [Electronic Version]. Simulation Practice and Theory,
26
Vol. 8, No. 5, Pp. 321-339.
Miser, H. J., & Quade, E. S. (1985). Handbook of Systems Analysis: Overview of Uses,
Procedures, Applications, and Practice. Chichester: John Wiley & Sons Ltd.
Mohapatra, P.K J.; Bora, M.C.; Sahu, K.C. (1984) Incorporating Delphi Results in
System Dynamics Models: A Case of Indian Tea Industry [Electronic version].
Technological Forecasting and Social Change, Vol. 25, No. 2, Pp. 159-177.
Png, I. (1998) Managerial economics. Malden: Blackwell. Pp. 99-103, 106-109.
Rauch, J., & Plooy, K. d. (2003). Multiproduct plants. Weinheim: Wiley-VCH GmbH
& Co. KgaA.
Roberts, E.B. (ed.) (1978) Managerial applications of system dynamics. Cambridge:
Productivity Press
Romme, G. (1994) Changing Business Systems in the European Paper and Pulp
Industry [Electronic version]. European Management Jourmal, Vol. 12, No. 4, Pg.
469 - 479.
Schwartz, P. (1997) The Art of the Long View: Planning for the Future in an Uncertain
World. Chichester: John Wiley & Sons. Pp. 3- 6, 100 - 117, 241 - 248.
Sterman, J. (1984) Appropriate summary statistics for evaluating the historical data of
System Dynamics models. Dynamica, Vol. 10, Part 2, Pp. 51 - 66.
Thorpe, Scott (2000) How to Think Like Einstein: Simple Ways to Solve Impossible
Problems. Naperville: Sourcebooks Inc.
Tromborg, E.; Buongiorno, J.; Solberg, B. (2000) The global timber market:
implications of changes in economic growth, timber supply, and technological
trends [Electronic version]. Forest Policy and Economics, Vol. 1, No. 1, Pp. 53-69
Vereniging van Nederlandse Papier- en kartonfabrieken - VNP (2002) Jaarverslag
2002 - Myth or reality: A new paper machine in the Netherlands? [Electronic
version]. Hoofddorp / The Hague: V NP / Stupers Van der Heijden.
Wu, Bin (2000) Manufacturing and Supply Systems Management: A Unified
Framework of Systems Design and Operation. London: Springer. Pp. 45 - 46, 52.
Zittema, S (2005) Waste Paper Mining (WPM) Fibre Mining from Recovered Paper
(Positioning Paper).
8. Appendix
Appendix 1: Input values for External Factors
Mega Trend External Factor Value Decreasing Increasing
Demand-shift for P&B products | Average Consumption per Capita -0.035* -0.038* -0.031*
Social Improvement in Collection System 0.0102 0.0051 0.0153
awareness % Collected P&B for NL 0.3 0.15 0.45
for the use of % Recovered P&B 0.7488 0.3799 1
recycled % Wood Pulp Production. -0.0067 -0.0038 -0.0105
material Annual Average Raw Material Cost 327.43 491.15 163.72
Business Reserve Threshold 600000000 | 900000000 | 300000000
environment in Current Capacity Divestment Threshold 0.2 0.3 0.1
the Netherlands % Reserve for Investment 0.1 0.05 0.15
* This value increases the initial shift of the special construction of this variable model equation (See footnote 2).
27
Appendix 2: Reference values for capacity and investment per production function
Production Function Capacity (tonnes) Investment (€)
Wood Pulp Production 700 000 400 000 000
Recycled Fibres Production 700 000 310 000 000
P&B Production 200 000 300 000 000
Appendix 3: Capacities in relation with environmental scenarios
Environmental Scenario
New Facility’s Set-up ® £ Qe 2, @ oe
New Fibres Production = Ee LC MC Ee sc
Recycled Fibres Production LC MC - - sc -
P&B Production with new fibres = = LC MC = Sc
P&B Production with recycled fibres LC MC - - Sc -
P&B Production with mixed fibres LC MC os Sc
SC: Small Capacity MC: Medium Capacity LC: Large Capacity
Appendix 4: Adjusted capacities for the new facilities’ set-ups
New Facility with One Production Function
Size Recycled Fibres Production New Fibres Production
Capacity (ton) Investment (€) Capacity (ton) Investment (€)
Small 350000 197556897 350000 254912125
Medium 700000 310000000 700000 400000000
Large 1050000 403479071 1050000 520618156
New Facility with Two Production Function
P&B Production Recycled Fibres Production New Fibres Production
Size Capacity Investment Capacity Investment Capacity Investment
(ton) (€) (ton) (€) (ton) ©
Small 100000 191184094 150376 114081152 140351 140746013
Medium 200000 300000000 300752 179012516 280702 220854167
Large 300000 390463617 451128 232992914 421053 287451723
New Facility with Three Production Function
P&B Production Recycled Fibres Production New Fibres Production
Size Capacity Investment Capacity Investment Capacity Investment
(ton) ©). (ton) © (ton) (3)
Small 100000 191184094 112602 94526089 35256 57338835
Medium 200000. 300000000 225203 148327333 70512 89974276
Large 300000 390463617 337805 193054757 105768 117105604
28
Scenario Analysis using System Dynamics M odelling:
The case of Production Portfolio Change in the Dutch Paper
and Board Industry (Supporting Material)
1. Dutch P& BI model equations
The structure of the model equations of the Dutch P&BI model is as follows:
Element type (Level, Auxiliary - including Rates -, Constant), Variable name
{variable type (Boolean, Integer, Real or Complex); variable unit; variable
definition; inflow {}; outflow {}}
The previously defined units for the Dutch P&BI model appear in table SM1.
Table SM1: Dutch P &BI system basic units
Unit Unit Information
EUR {def _ CURRENCY("EUR"); doc Euro}
kg {def __ KILOGRAM; doc Kilogram — Mass}
P {def ATOMIC; doc person}
tn {def kg*1000, doc tonne}
It is possible to enter units from the list, which were previously defined in the, or let
the package derive the units from the equations by ticking in the verification box. The
model equation indicates the former situation by adding ‘unit’ in the model equation
while in the later situation appears ‘autounit’.
Table SM2 presents the model equations of the quantitative model of the Dutch
P&BI system, ordered by element type.
Table SM2: Model equations of the Dutch P&BI system
Element Information
% Collected P&B for NL {autotype Real; def .3}
% Imported P&B {autotype Real; def 3.5)
% P&B for NL {autotype Real; def 0.3}
% Recovered P&B {autotype Real; def 0.7488; }
‘Accumulation Period {autotype Real; unit yr; def 0.08}
‘Ageing of Machinery Coefficient {autotype Real; unit 1/yr; def 0.055)
in Compensation’}
Annual Divestment Cost {autotype Real; autounit EUR/yr; def ‘Average Annual Compensation™ "Persons
Pulp'+'Recovered P&B Rate'+'Wood Pulp Production’)}
Annual Energy Cost {autotype Real; autounit EUR/yr; def ‘Annual Unitary Energy Cost™*(‘Processing
Annual Labour Cost {autotype Real; autounit EUR/yr; def Employees*”Average Annual Compensation’}
Processing Pulp Capacity'+'Current; Recycling P&B Capacity'+'Current Wood Pulp Capacity’) }
Annual Maintenance Cost {autotype Real; autounit EUR/yr; def ‘Unitary Maintenance Cost’*(‘Current
Annual Other Cost {autotype Real; autounit EUR/yr; def ‘Annual Unitary Other Cost'Processing Pulp’}
Production')}
Annual Raw Material Cost {autotype Real; autounit EUR/yr; def ‘Average Unitary Raw Material
Cost’*('Foreign Recovered P&B Rate'+'Purchased; Amount Wood Pulp'+'Recovered P&B Rate'+'Wood Pulp
Annual Unitary Energy Cost {autotype Real; unit EUR/tn; def 23.82)
Annual Unitary Other Cost {autotype Real; unit EUR/tn; def 63.53}
Average Annual Compensation {autotype Real; unit EUR/(yr*p); def 57000}
Average Unitary Raw Material Cost {autotype Real; unit EUR/tn; def 327.43}
Collection Period {autotype Real; unit yr; def 0.04}
Element
Element Information
Compensation period {autotype Real; unit yr; def 10}
Current Processing Pulp Capacity Utilisation {autotype Real; def ‘Processing Pulp'/'Current Processing Pulp
Capacity’}
Current Processing Pulp Reduction {autotype Real; autounit tn/yr2; def ‘Processing Pulp Divestment
Multiplier'*(‘Current Processing Pulp Capacity'-('Processing Pulp!/'Processing Pulp Capacity Threshold for
Divestment}))/1<<yr>>}
Current Recycling P&B Capacity Utilisation {autotype Real; def 'DP&BI Recycling P&B/‘Current Recycling
P&B Capacity'}
Current Recycling P&B Expansion {autotype Real, autounit tn/yr2; def (‘Expected Recycling P&B
Capacity'-'Current Recycling P&B Capacity’)/‘Investment Period}
Current Recycling P&B Reduction {autotype Real; autounit tn/yr?; def ‘Recycling P&B Divestment
Multiplier'*(‘Current Recycling P&B Capacity'-('DP&BI Recycling P&B'/'Recycling P&B Capacity Threshold for
Divestment’))/1<<yr>>}
Au
Current Wood Pulp Capacity Utilisation {autotype Real; def 'Wood Pulp Production’/Current Wood Pulp
Capacity'}
‘Auxiliary
Current Wood Pulp Reduction {autotype Real; autounit tn/yr?; def ‘Wood Pulp Divestment
Multiplier’*('Current Wood Pulp Capacity'-(‘Wood Pulp Production'/"Wood Pulp Capacity Threshold for
Divestment’))/1<<yr>>}
Decline {autotype Real; unit p/yr; def 'NL Decline Index™'NL Population’}
Depreciation Period {autotype Real; unit yr; def 25)
Disposal Rate {autotype Real, autounit tn/yr, def (NL P&B Accumulation*(1-NL %
Collection’)/‘Accumulation Period')}
DP&BI Recycling P&B {autotype Real; autounit tn/yr; def MIN(Raw Material Requirement*"% Recovered
P&B, ‘Current Recycling P&B Capacity’)}
End of Compensation {autotype Real; autounit p/yr; def ‘Persons in Compensation’/'Compensation
period’; }
Expected Processing Pulp Expansion {autotype Real; autounit tn/yr2; def ‘Processing P&B Investment to
Capacity*'Processing Pulp Investment Delay’}
Expected Processing Pulp Reduction {autotype Real; autounit tn/yr?; def ‘Current Processing Pulp
Reduction'}
‘Auxiliary
Expected Recycling P&B Expansion {autotype Real; autounit tn/yr2; def ‘Recycling P&B Investment
Delay’*'Recycling P&B Investment to Capacity'}
itary
Expected Recycling P&B Reduction {autotype Real; autounit tn/yr?; def ‘Current Recycling P&B
Reduction’}
Expected Wood Pulp Expansion {autotype Real; autounit tn/yr2; def ‘Wood Pulp Investment to
Capacity*'Wood Pulp Investment Delay’}
Expected Wood Pulp Reduction {autotype Real; autounit tn/yr2; def ‘Current Wood Pulp Reduction’}
Foreign Consumption Rate {autotype Real; autounit tn/yr; def ‘Foreign Population’*Foreign Average
Consumption per Capita'}
Foreign Disposal Rate {autotype Real; autounit tn/yr; def ((1-Foreign % Collection’)*Foreign Paper
Accumulation’)/‘Accumulation Period'}
Foreign Growth {autotype Real; unit p/yr; def 971587.9}
Foreign P&B Collection Rate {autotype Real; autounit tn/yr; def (‘Foreign % Collection™Foreign Paper
Accumulation’)/'Accumulation Period'}
Foreign Recovered P&B Rate {autotype Real; unit tn/yr; def MIN(IF(((‘% Recovered P&B™'Raw Material
Requirement')-'NL Recovered P&B Rate')<0<<tn/yr>>,0<<tn/yr>>,(('% Recovered P&B*'Raw Material
Requirement’)-'NL Recovered P&B Rate’)), ‘Foreign P&B Collection Rate')}
Growth {autotype Real; unit p/yr; def 'NL Growth Index™"NL Population’}
Hiring {autotype Real; autounit p/yr; def (‘Current Recycling P&B Expansion’/‘Recycling P&B Capacity to
Labour’)+(‘Processing Pulp Expansion'/'Processing Pulp Capacity to Labour’)+('Wood Pulp Expansion'/'Wood
Pulp Capacity to Labour')}
Imported P&B {autotype Real; autounit tn/yr; def (‘P&B NL Sales')*"% Imported P&B}
Increase in Foreign % Collection {autotype Real; unit 1/yr; def 0.0137)
Increase in Foreign Consumption per Capita {autotype Real; unit tn/(yr\2*p); def 0.0045)
Increase in NL % Collection {autotype Real; unit 1/yr; def 0.0102}
Increase in NL Consumption per Capita {autotype Real; unit tn/(yr2*p), def
0.005<<tn/(yr*2*p)>>+0.001<<tn/(yr2*p)>>*COSWAVE(20,5<<yr>>,2.5<<yr>>)+STEP(0.03<<tn/(y
rA2*p)>>,STARTTIME+7<<yr>>)+STEP(-0.037<<tn/(yr2*p)>> STARTTIME+9<<yr>>)}
Increase of % Waste {autotype Real; unit 1/yr; def 0.0049}
Increase of Raw Material {autotype Real; unit 1/yr; def 0.0058}
Increase Unitary Maintenance Cost {autotype Real; autounit EUR/(yr*tn); def ‘Ageing of Machinery
Coefficient’*'Unitary Maintenance Cost'}
Investment Delay {autotype Real; unit yr; def 1}
Investment Period {autotype Real; unit yr; def 4}
Element
Element Information
Last Year Profits {autotype Real; autounit EUR/yr; def DELAYPPL(Total Profits 1<<yr>>)}
Last Year’s P&B Sales {autotype Real; autounit tn/yr; def DELAYPPL('P&B Intemational Sales'+"P&B NL
Sales',1<<yr>>)}
Layoffs {autotype Real; autounit p/yr; def (‘Current Recycling P&B Reduction'/Recycling P&B Capacity to
Labour')+(‘Current Processing Pulp Reduction'/'Processing Pulp Capacity to Labour')+('Current Wood Pulp
Reduction'/'Wood Pulp Capacity to Labour')}
Net Inflow for Reserve {autotype Real; autounit EUR/yr; def '% Reserve’*'Total Profits'}
NL Collected P&B Export Rate {autotype Real; autounit tn/yr; def ((1-% Collected P&B for NL)*"NL P&B
Collection'/‘Collection Period’)}
NL Consumption {autotype Real; autounit tn/yr; def 'NL Population’"NL Average Consumption per
Capita’}
NL Decline Index {autotype Real; unit 1/yr; def 0.0087)
NL Growth Index {autotype Real; unit 1/yr; def 0.015}
NL Recovered P&B Rate {autotype Real; autounit tn/yr; def (% Collected P&B for NL*NL P&B
Collection’/'Collection Period’)}
P&B Collection Rate {autotype Real; autounit tn/yr; def (‘NL P&B Accumulation*NL %
Collection'/‘Accumulation Period')}
P&B International Sales {autotype Real; autounit tn/yr; def (((1-"% P&B for NL')*P&B Consumption
Forecast'))}
P&B NL Sales {autotype Real; autounit tn/yr, def ('% P&B for NL*P&B Consumption Forecast})}
P&B Sales Change {autotype Real; autounit tn/yr; def ‘Last Years P&B Sales'+'P&B Sales Difference’; }
P&B Sales Difference {autotype Real; autounit tn/yr; def (‘P&B International Sales'+'P&B NL Sales')-'Last
Years P&B Sales'}
P&B Sales Forecast {autotype Real; autounit tn/yr; def MIN(P&B Consumption Forecast’,,P&B Sales
Change’)}
Processed P&B for NL Consumption {autotype Real; autounit tn/yr, def MIN(Imported P&B+'P&B NL
Sales','NL Consumption')}
Processing P&B Investment to Capacity {autotype Real; unit tn/(yr*EUR); def 0.001)
Processing Pulp {autotype Real; autounit tn/yr; def MIN(‘Current Processing Pulp Capacity’,P&B Sales
Forecast')}
Processing Pulp Capacity Threshold for Divestment {autotype Real; def 0.2)
Processing Pulp Capacity Threshold for Investment {autotype Real; def 0.9}
Processing Pulp Capacity to Labour {autotype Real; unit tn/(p*yr); def 10000}
Processing Pulp Depreciation {autotype Real; autounit EUR/yr; def ‘Processing P&B Capital
Stock’/'Depreciation Period'}
Processing Pulp Divestment Multiplier {autotype Real; def IF(‘Current Processing Pulp Capacity
Utilisation'<'Processing Pulp Capacity Threshold for Divestment’ AND ‘P&B Sales
Change'<0<<tn/yr>>,1,0,0)}
Processing Pulp Expansion {autotype Real, autounit tn/yr2; def (‘Expected Processing Pulp Capacity’-
‘Current Processing Pulp Capacity’)/‘Investment Period'}
Processing Pulp Expected Capacity Utilisation {autotype Real; def ‘Processing Pulp'/'Expected Processing
Pulp Capacity'}
Processing Pulp Investment {autotype Real, autounit EUR/yr; def ‘Processing Pulp Investment
Multiplier'*'Processing P&B Investment Requirement'/1<<yr>>}
Processing Pulp Investment Budget Consumption {autotype Real; autounit EUR/yr; def ‘Processing Pulp
Investment Budget /‘Investment Period'}
Processing Pulp Investment Delay {autotype Real; autounit EUR/yr; def DELAYPPL(Processing Pulp
Investment!,1<<yr>>)}
Processing Pulp Investment Multiplier {autotype Real; def IF(Reserve for Investments'>'Reserve
Threshold’ AND ‘Processing Pulp Expected Capacity Utilisation'>'Processing Pulp Capacity Threshold for
Investment! AND ‘Profits Moving Average'>0<<EUR/yr>> AND 'P&B Sales Change'>0<<tn/yr>>, 1,0,0)}
Profits Moving Average {autotype Real; autounit EUR/yr; def (‘Total Profits'+'Last Year Profits'+'Two
Years Ago Profits')/3}
Purchased Amount Wood Pulp {autotype Real; autounit tn/yr; def (1-% Wood Pulp Production’)*Wood
Pulp Requirement'}
Raw Material Requirement {autotype Real; autounit tn/yr; def 'P&B Sales Forecast™*(‘Raw Material Need'-
'% Non-Fibrous Material’)
Recovered P&B Rate {autotype Real, autounit tn/yr; def MIN(('% Recovered P&B*Raw Material
Requirement’),'NL Recovered P&B Rate’)}
Recycling P&B Capacity Threshold for Divestment {autotype Real; def 0.2}
Recycling P&B Capacity Threshold for Investment {autotype Real; def 0.9}
Recycling P&B Capacity to Labour {autotype Real; unit tn/(p*yr); def 10000}
Recycling P&B Depreciation {autotype Real; autounit EUR/yr, def ‘Recycling P&B Capital
Stock'/'Depreciation Period’
Element
Type
Element Information
Recycling P&B Divestment Multiplier {autotype Real; def IF(Current Recycling P&B Capacity
Utilisation'<'Recycling P&B Capacity Threshold for Divestment’ AND ‘P&B Sales
Change'<0<<tn/yr>>,1,0,0)}
Recycling P&B Expected Capacity Utilisation {autotype Real; def 'DP&BI Recycling P&B’/Expected
Recycling P&B Capacity’
Recycling P&B Investment {autotype Real; autounit EUR/yr; def ‘Recycling P&B Investment
Multiplier'*'Recycling P&B Investment Requirement'/1<<yr>>}
Recycling P&B Investment Consumption {autotype Real; autounit EUR/yr; def ‘Recycling P&B Investment
Budget!/'Investment Period’
Recycling P&B Investment Delay {autotype Real; autounit EUR/yr; def DELAYPPL(‘Recycling P&B
Investment; ‘Investment Delay’)}
Recycling P&B Investment Multiplier {autotype Real; def IF(‘Reserve for Investments'>'Reserve Threshold"
AND ‘Recycling P&B Expected Capacity Utilisation'>'Recycling P&B Capacity Threshold for Investment’ AND
'Profits Moving Average'>0<<EUR/yr>> AND 'P&B Sales Change'>0<<tn/yr>>,1,0,0)}
Recycling P&B Investment to Capacity {autotype Real; unit tn/(yr*EUR); def 0.004}
Total Cost {autotype Real; autounit EUR/yr; def ‘Annual Divestment Cost'+'Annual Energy Cost'+'Annual
Maintenance Cost'+'Annual Other Cost'+'Annual Raw Material Cost'+'Annual Labour Cost'+'Processing Pulp
Depreciation'+'Recycling P&B Depreciation'+'Wood Pulp Depreciation’}
Total Profits {autotype Real; autounit EUR/yr; def ‘Total Revenues'-Total Cost’}
Total Revenues {autotype Real; autounit EUR/yr; def ‘Average Price per ton of P&B*('P&B NL
Sales'+'P&B International Sales')}
Two Years Ago Profits {autotype Real; autounit EUR/yr; def DELAYPPL( Total Profits'2<<yr>>)}
Variation in P&B Consumption Forecast {autotype Real; unit tn/yr*2; def (‘NL Consumption’-'P&B
Consumption Forecast')/14<<yr>>}
Variation of % NL Wood Pulp Production {autotype Real; autounit yr*-1; def IF(‘% Wood Pulp
Production'>0,-0.0067<<1/yr>>,0<<1/yr>>,0<<1/yr>>)}
Variation of Non-Fibrous Material {autotype Real; autounit yr*-1; def IF(‘% Non-Fibrous Material’>0,-
0.0037<<t/yr>>,0<<1/yr>>,0<<1/yr>>)}
Variation of Price per ton of P&B {autotype Real, autounit EUR/(yr*tn), def
10<<EUR/(tn*yr)> >+2.5<<EUR/(tn*yr)>>*COSWAVE(25,5<<yr>>,3.5<<yr>>)}
Waste {autotype Real; autounit tn/yr; def '% Waste™ Processing Pulp’}
Wood Pulp Capacity Threshold for Divestment {autotype Real; def 0.2}
Wood Pulp Capacity Threshold for Investment {autotype Real; def 0.9}
Wood Pulp Capacity to Labour {autotype Real; unit tn/(p*yr); def 10000)
Wood Pulp Depreciation {autotype Real; autounit EUR/yr; def ‘Wood Pulp Capital Stock//Depreciation
Period’}
Wood Pulp Divestment Multiplier {autotype Real; def IF(Current Wood Pulp Capacity Utilisation'<'Wood
Pulp Capacity Threshold for Divestment',1,0,0)}
Wood Pulp Expansion {autotype Real; autounit tn/yr2; def (‘Expected Wood Pulp Capacity’'Current
Wood Pulp Capacity’)/'Investment Period’}
Wood Pulp Expected Capacity Utilisation {autotype Real; def ‘Wood Pulp Production’/'Expected Wood Pulp
Capacity’}
Wood Pulp Investment {autotype Real; autounit EUR/yr; def ‘Wood Pulp Investment Multiplier*'Wood
Pulp Investment Requirement'/1<<yr>>}
Wood Pulp Investment Consumption {autotype Real; autounit EUR/yr; def ‘Wood Pulp Investment
Budget!/'Investment Period"
Wood Pulp Investment Delay {autotype Real; autounit EUR/yr; def DELAYPPL(Wood Pulp
Investment!1<<yr>>)}
Wood Pulp Investment Multiplier {autotype Real, def IF(Reserve for Investments'>'Reserve Threshold’
AND 'Wood Pulp Expected Capacity Utilisation'>'Wood Pulp Capacity Threshold for Investment’ AND ‘Profits
Moving Average'>0<<EUR/yr>> AND 'P&B Sales Change'>0<<tn/yr>>, 1,0,0)}
Wood Pulp Investment to Capacity {autotype Real; unit tn/(yr*EUR); def 0.005}
Wood Pulp Production {autotype Real; autounit tn/yr; def MIN('% Wood Pulp Production™"Wood Pulp
Requirement’, ‘Current Wood Pulp Capacity’)}
‘Auxiliary | Wood Pulp Requirement {autotype Real; autounit tn/yr; def (1-% Recovered P&B')*Raw Material
Requirement'}}
Constant | % Reserve {autotype Real; init 0.1}
Constant | Processing P&B Investment Requirement {autotype Real, unit EUR; init 300000000; }
Constant | Recycling P&B Investment Requirement {autotype Real; unit EUR; init 310000000}
Constant _| Reserve Threshold {autotype Real; unit EUR; init 500000000}
Constant | Wood Pulp Investment Requirement {autotype Real, unit EUR; init 400000000)
Level % Non-Fibrous Material {autotype Real; init 0.1178; inflow { autodef ‘Variation of Non-Fibrous Material’
as
Level % Waste {autotype Real; init 0.0344; inflow { autodef ‘Increase of % Waste! }}
Element
Element Information
Type
Level % Wood Pulp Production {autotype Real; init 0.2165, inflow { autodef ‘Variation of % NL Wood Pulp
Production’ }}
Level ‘Average Price per ton of P&B {autotype Real; unit EUR/tn; init 600; inflow { autodef ‘Variation of Price
per ton of P&B' }}
Level Current Processing Pulp Capacity {autotype Real; unit tn/yr; init 5000000; inflow { autodef ‘Processing
Pulp Expansion’ }; outflow { autodef ‘Current Processing Pulp Reduction’ }}
Level Current Recycling P&B Capacity {autotype Real; unit tn/yr; init 3500000; inflow { autodef ‘Current
Recycling P&B Expansion’ }; outflow { autodef ‘Current Recycling P&B Reduction’ }}
Level Current Wood Pulp Capacity {autotype Real; unit tn/yr; init 160000; inflow { autodef ‘Wood Pulp
Expansion’ }; outflow { autodef ‘Current Wood Pulp Reduction’ }}
Level Employees {autotype Real; unit p; init 6300; outflow { autodef Layoffs }, inflow { autodef Hirings }}
Level Expected Processing Pulp Capacity {autotype Real; unit tn/yr; init 5000000; inflow { autodef ‘Expected
Processing Pulp Expansion! }; outflow { autodef ‘Expected Processing Pulp Reduction’ }}
Level Expected Recycling P&B Capacity {autotype Real; unit tn/yr; init 3500000; inflow { autodef ‘Expected
Recycling P&B Expansion’ }; outflow { autodef ‘Expected Recycling P&B Reduction’ }}
Level Expected Wood Pulp Capacity {autotype Real; unit tn/yr; init 160000; inflow { autodef ‘Expected Wood
Pulp Expansion’ }; outflow { autodef ‘Expected Wood Pulp Reduction’ }}
Level Foreign % Collection {autotype Real; init 0.3824; inflow { autodef ‘Increase in Foreign % Collection’ }}
Level Foreign Average Consumption per Capita {autotype Real; unit tn/(yr*p); init 0.1342; inflow { autodef
‘Increase in Foreign Consumption per Capita’ }}
Level Foreign Paper Accumulation {autotype Real; unit tn; init 7128600; inflow { autodef ‘Foreign
Consumption Rate’ }; outflow { autodef ‘Foreign P&B Collection Rate’ }; outflow { autodef 'Foreign
Disposal Rate’ }}
Level Foreign Population {autotype Real; unit p; init 427306192.3; inflow { autodef ‘Foreign Growth’ }}
Level NL % Collection {autotype Real; init 0.5718; inflow { autodef ‘Increase in NL % Collection’ }}
Level NL Average Consumption per Capita {autotype Real; unit tn/(yr*p); init 0.21; inflow { autodef ‘Increase
in NL Consumption per Capita’ }}
Level NL Converted P&B {autotype Real; unit tn; init 10000000, outflow { autodef ‘Processed P&B for NL
Consumption’ }; inflow { autodef ‘Imported P&B’ }; inflow { autodef 'P&B NL Sales' }}
Level NL P&B Accumulation {autotype Real; unit tn; init 250000; inflow { autodef ‘Processed P&B for NL
Consumption’ }; outflow { autodef ‘Disposal Rate’ }; outflow { autodef 'P&B Collection Rate’ }}
Level NL P&B Collection {autotype Real; unit tn; init 1746000, outflow { autodef ‘NL Recovered P&B Rate’ };
outflow { autodef 'NL Collected P&B Export Rate }; inflow { autodef 'P&B Collection Rate’ }}
Level NL Population {autotype Real; unit p; init 15010000; outflow { autodef Decline }; inflow { autodef
Growth }}
Level NL Stock Wood Pulp {autotype Real; unit tn; init 6000000; inflow { autodef ‘Purchased Amount Wood
Pulp' }; outflow { autodef ‘Processing Pulp’ }; outflow { autodef Waste }; inflow { autodef 'DP&BI
Recycling P&B" }; inflow { autodef ‘Wood Pulp Production’ }}
Level P&B Consumption Forecast {autotype Real; unit tn/yr; init 2778538.462; inflow { autodef ‘Variation in
P&B Consumption Forecast’ }}
Level Persons in Compensation {autotype Real; unit p; init 0; inflow { autodef Layoffs }; outflow { autodef
‘End of Compensation’ }}
Level Processing P&B Capital Stock {autotype Real, unit EUR; init 7500000000; inflow { autodef ‘Processing
Pulp Investment Budget Consumption’ }; outflow { autodef ‘Processing Pulp Depreciation’ }}
Level Processing Pulp Investment Budget {autotype Real; unit EUR; init 0; outflow { autodef ‘Processing Pulp
Investment Budget Consumption' }; inflow { autodef ‘Processing Pulp Investment’ }}
Level Raw Material Need {autotype Real; init 1.0341, inflow { autodef ‘Increase of Raw Material’ }}
Level Recovered P&B Stock {autotype Real; unit tn; init 96000; inflow { autodef ‘Recovered P&B Rate’ };
outflow { autodef 'DP&BI Recycling P&B' }; inflow { autodef ‘Foreign Recovered P&B Rate’ }}
Level Recycling P&B Capital Stock {autotype Real; unit EUR; init 1550000000; inflow { autodef ‘Recycling
P&B Investment Consumption’ }; outflow { autodef ‘Recycling P&B Depreciation’ }}
Level Recycling P&B Investment Budget {autotype Real, unit EUR; init 0; outflow { autodef ‘Recycling P&B
Investment Consumption’ }; inflow { autodef ‘Recycling P&B Investment! }}
Level Reserve for Investments {autotype Real; unit EUR; init 500000000; inflow { autodef ‘Net Inflow for
Reserve’ }; outflow { autodef ‘Recycling P&B Investment’ }; outflow { autodef ‘Processing Pulp
Investment’ }; outflow { autodef ‘Wood Pulp Investment }}
Level Stock P&B {autotype Real; unit tn; init 54500; inflow { autodef ‘Processing Pulp' }; outflow { autodef
'P&B International Sales’ }; outflow { autodef 'P&B NL Sales' }}
Level Unitary Maintenance Cost {autotype Real; unit EUR/tn; init 10, inflow { autodef ‘Increase Unitary
Maintenance Cost' }}
Level Wood Pulp Capital Stock {autotype Real; unit EUR, init 1600000; inflow { autodef ‘Wood Pulp
Investment Consumption’ }; outflow { autodef ‘Wood Pulp Depreciation’ }}
Level Wood Pulp Investment Budget {autotype Real, unit EUR; init 0; outflow { autodef ‘Wood Pulp
Investment Consumption’
; inflow { autodef ‘Wood Pulp Investment’ }
2. Specification of New Facilities
This section presents the design of the five set-ups for a new facility, ie. a recycling
P&B pulp plant, a wood pulp plant, a P&B plant using wood pulp; a P&B plant using
recycled fibres, a P&B plant using wood pulp and a P&B plant using wood pulp and
recycled fibres.
Figure SM1 portrays the graphical representation in the simulation model for the case of
a new facility with one production function, i.e. the production of pulp from recycled
fibres.
Once an investment budget is available, it will reduce in a delay construction that
depends on the investment period. This flow will feed the capital stock, which will
reduce in a delay construction that takes into account the depreciation period.
NF Recyé
Investme|
Consu|
ling P&B
it Budget
[notion
NF Recycling P&B
Depreciation
>)
NF Recycling PRB
Investment Budget
NF Investment
Period
New Facility Recycled Fibres
Investment Transition
3 |
New Facility Recycled Fibres Capital Stock
NF Recycling P&B
Capital Stock
NF Depreciation
NF Expected
Recycling P&B
Capacity
NF Recycling P&B
Current Expansion
NF Investment
Period
New Facility Recycled Fibres Capacity Adjustment
NF Recycling P&B
Current Capacty
NF Recycled Fibres
Annual Revenues
NF Recycled Fibres
Annual Cost
NF Recyded Fibres
Cummuiative Annual
Profits
NF Recycling =/
NF Recycled Fibres NF Recycied Fibres
Sales Operating Costs
NF Recycling P&B
Depreciation
NF Recycled Fibres
Price
NF Recycling P&B
[New Facility Recycled Fibres Profits Waste
NL Recovered P&B
Rate
NF Recyding P&B
Current Capacty
NF Recycled Fibres
Sales
Foreign PaB T
Collection Rate
7Y NF Recycled Fibres 7.
Aoi Mepeerdeas INF Recycing P&B
a
a)
| Stock
NF Recycled Fibres
Foreign Recovered,
Pas Rate
NF Recycled Fibres
Recovered P&B
Requirement
o—
New Facility for Recycled Fibres
[ivr Recovered Pam
NF Recycled Fibres
‘Stock
NF Recycling P&B
NF % Waste *
Figure SM1: New Facility for Recycling Pulp Production
At the same time, the current capacity will start to build up in a goal-seeking
construction that combines the expected capacity, the current capacity and the
investment period.
After the investment period has passed, the new facility starts buying raw
material for the production process; in this case, it is recovered P&B. The raw material
(recovered P&B) is transformed at the current capacity and at the same time waste is
produced in relation with the production rate. Afterwards, the final product is ready for
sales.
The sales of recycled fibres and the price serve to calculate the revenues. The
costs depend on the production function, the produced waste, the operation costs and the
depreciation. The revenues and costs provide the cumulative profits of the new facility.
Figure SM2 portrays the graphical representation in the simulation model for the case of
a new facility with one production function, i.e. the production of wood pulp.
— ——~ og)
iow cy wis Pup Praca
feted tow Hctty Weed Pulp Proccon Copta Sc
NF Wood Pulp
Expected Capacity
NF Wood Pulp
Cumulative Annual Ae)
ie NF Wood Pulp
Depreciation
NF Wood Pulp O
Current Expansion NF Wood Pulp Price
NF Wood Pulp van’ NF Wood Pulp
Van ee Current Capacity OO Transformation _
XY, NF Wood Pulp Sales
NF tavestment iSO) gli Wand Ri
Period NF Wood Pulp OPerating Costs
Waste
[New Facility Wood Pulp Production Capacity Adjustment ‘New Facility Wood Pulp Production Profits
NF Wood Pulp
Current Capacity
ir NF Wood Pulp
‘Transformation
)
NF Wood Pulp
KD waste
NF Wood Pulp
Pulpwood Rate
NF Wood Pulp Sales A
NE Wood Pulp
Pulpwood Stock
wei, Ch
Pulpwood Purchase ——
New Facility for Wood Pulp Production
Figure SM2: New Facility for Wood Pulp Production
Once an investment budget for the wood pulp production is available, it will
reduce in a delay construction that depends on the investment period. This flow will
feed the capital stock, which will reduce in a delay construction that takes into account
the depreciation period.
At the same time, the current capacity of the wood pulp production function will
start to build up in a goal-seeking construction that combines the expected capacity, the
current capacity and the investment period.
After the investment period has passed, the new facility starts buying raw
material for the production process; in this case, it is pulpwood. The calculation of the
raw material purchase depends on the capacity of the production function and the %
waste. The pulpwood is transformed at the current capacity and at the same time waste
is produced in relation with the production rate. Afterwards, the final product is ready
for sales.
The sales of new wood fibres and the price serve to calculate the revenues. The
costs depend on the produced amount of new wood fibres, the produced waste, the
operation costs and the depreciation. The revenues and costs provide the cumulative
profits of this new facility.
Figure SM3 presents the graphical representation in the simulation model for the case of
a new facility with two production functions, i.e. the production of wood pulp and P&B.
TF PRB Wo]
Pulpng In
aah
Pulping Investment ‘al
NF P&B Wood Pulp
‘anual Revenues
NF P&B Wood Pulp
NF P&B Wood Pulp
INF Investment
NF P&B Wood Pulp
“Transformation
Imestment Budget
‘Consumption,
NF 4
(8 Waod Pulp
Capital Sack
[New Facility P&B Wood Pulp Capital Stock
ceneaien © A
Cummulative Anna
NF P&E Wood Pulp
NF Depredation Pulping
NF PRE Wood Pulp
NF P&B Wood Pulp
aaa Pulping Waste
New Facility P&B Wood Pulp Profits
“Transformation
NF P&B Wood Pulp
Annual Cost
NF P&B Wood Pulp
jepredation
NF P&B Wood Pulp
=, Operating Costs
Waste
NF P&B Wood Pulp
‘Transformation
NF P&B Wood Pulp
"Transformation
Investment Budget
INew Facility P&B Wood Pulp
linvestment Transition
NF P&B Wood Pulp
Pulping Expected
NF P&B Wood Pulp
Capacity
‘Tr refarmation
expeaee Capacty
NF P&B Wood Pulp
Pulping Current
Exparsion
NF Fae Wood Pulp
Pulping Current.
Capacty py
INF investment
Period
[New Facility P&B Wood Pulp Capacity Adjustment
NF P&B Wood Pulp
"Tranefarmation|
Current Exparsion
NF P&B Wood Pulp
‘Teensfarmation
Currant Capacity
NF P&B Wood Pulp
Pubpwood Rate
Q
NF P&B Wood Pulp
Pulpwood Purchase
New Facility for P&B Wood Pulp
NF P&B Wood Pulp
Pulping Current
Capacty
NF Pa Wood Pulp
Pulpwood Stock
ee)
Pulping % Waste
NE P&B Wood Pulp
“Transformation
ae
NF P&S Wood Pulp
Fibres Stock
NF P&B Wood Pulp
Pulping
nae
NF P&B Wood Pulp
“Transformation
Waste
NF P&B Wood Pulp
Pubiing Waste
f-—0
NF P&B Wood Pulp
‘Transformation %
NF P&B Wood Pulp
PRB Soles
NF P82 Wood Pulp P& O
B stock
Figure SM3: New Facility for Wood Pulp and P&B
Once an investment budget for the wood pulp production and the P&B transformation
are available, they will reduce in a delay construction that depends on the investment
period. This flow will feed the capital stock, which will reduce in a delay construction
that takes into account the depreciation period.
At the same time, the current capacity of the wood pulp and the P&B
transformation production functions will start to build up in a goal-seeking construction
that combines the expected capacity, the current capacity and the investment period.
After the investment period has passed, the new facility starts buying raw
material for the production process; in this case, it is pulpwood. The calculation of the
raw material purchase depends on the capacity of each production function and the %
waste of each production. The pulpwood is transformed at the current capacity and at
the same time waste is produced in relation with the production rate. Once the new
wood fibres are available, they become P&B products at the current capacity and at the
same time waste is produced in relation with the production rate. Afterwards, the final
product is ready for sales.
The sales of P&B products made from new wood fibres and the price serve to
calculate the revenues. The costs depend on the produced amount of new wood fibres,
the produced amount of P&B, the produced waste in each production function, the
operation costs and the depreciation. The revenues and costs provide the cumulative
profits of this new facility.
Figure SM4 shows the graphical representation in the simulation model for the case of a
new facility with two production functions, i.e. the production of recycled fibres and
P&B.
NF pa
nvestme
‘Consul
cycled
Budget
NF P8B Recycled ten
Recyeing Investment INF P&B Recycles
Budget Depreciation
TERA Recyaes
Captal Stock
IN investment
Periad
NF PAB Recycled
‘Consumption
IF Price parton of P&
@
NF P&B Recycled
Annual Revenues
Ne
NF PaBReqcled
NF PAB Recycled
‘annual Cast
PAB Recycled
TNF Pai Recycled
Depreciation
NF P&B Recycled
Operating Costs
NE Pa Recycled
“Transformation
Investment Budget
Expansio
New Facility Pas
Recycledinvestment Transition
Recyding Current
Now Faclity P&B RecycledCapacty Adjustment
NF P&B Recycled
Recyaing Current
‘Capacity
NF Invest
Period
‘raneformation P&S ving eo
we Depreciation || ne paBtnscing Pe NFPA Recycled O,
Pere Osaiee Transiorraten en
[New Facility P&B Recycled Capital Stock |New Facility P&B Recycled Profits sen Recycing P&B
NFP Recyded
necjlng Expected NF PAB Reece
expense Capacty
NF P88 Racy NF Pag Recyces
“Transformation
current expansion
€
NF P&B Recyded
“Transformation
Curent Capacity
NFPAB Recycles
NL Recovered PRB Recyding Current
INF PAB Recycled
NE Pas Recycled NFPAB Recycled %
Requremant Waste
Now Facility for P&B Recycled
THF PRB Recycled
Transformation Se
a ee coe “fanctornation
oe, Curent Capac
NF POB Recycled NL Ne paB Recyed NF Pa6 Recycies
NA Negvares Fab ate recrang Pa ‘antormation 8
N88 Recytng P&
ous
cotecton fate Ne peBRecyaea eae
Van’ Ne PAB Reed ores Stack ee Some
O— | Recovered Pas Stock
MF Pub Reqyded
Foreign tecverea NE PRB Recycing Sianebrneton
Beerate ecg P88
Figure SM4: New Facility for Recycled Fibres and P&B
Once an investment budget for the recycled fibres production and the P&B
transformation are available, they will reduce in a delay construction that depends on
the investment period. This flow will feed the capital stock, which will reduce in a
delay construction that takes into account the depreciation period.
At the same time, the current capacity of the recycled fibres and the P&B
transformation production functions will start to build up in a goal-seeking construction
that combines the expected capacity, the current capacity and the investment period.
After the investment period has passed, the new facility starts buying raw
material for the production process; in this case, it is recovered P&B. The calculation of
the raw material purchase depends on the capacity of each production function and the
% waste of each production. The recovered P&B is transformed at the current capacity
and at the same time waste is produced in relation with the production rate. Once the
recycled fibres are available, they become P&B products at the current capacity and at
the same time waste is produced in relation with the production rate. Afterwards, the
final product is ready for sales.
The sales of P&B products made from recycled fibres and the price serve to
calculate the revenues. The costs depend on the produced amount of recycled fibres, the
produced amount of P&B, the produced waste in each production function, the
operation costs and the depreciation. The revenues and costs provide the cumulative
profits of this new facility.
Figure SM5 presents the graphical representation in the simulation model for the case of
a new facility with three production functions, i.e. the production of wood pulp,
recycled fibres and P&B.
Once an investment budget for the wood pulp production, recycled fibres
production and the P&B transformation are available, they will reduce in a delay
construction that depends on the investment period. This flow will feed the capital
stock, which will reduce in a delay construction that takes into account the depreciation
period.
At the same time, the current capacity of the wood pulp, recycled fibres and the
P&B transformation production functions will start to build up in a goal-seeking
construction that combines the expected capacity, the current capacity and the
investment period.
After the investment period has passed, the new facility starts buying raw
material for the production process; in this case, it is pulpwood and recovered P&B.
The calculation of the raw material purchase depends on the capacity of each production
function and the % waste of each production. The pulpwood and the recovered P&B
are transformed at the current capacity and at the same time waste is produced in
relation with each production rate. Once the new and recycled fibres are available, they
become P&B products at the current capacity producing at the same time waste in
relation with the production rate. Afterwards, the final product is ready for sales.
The sales of P&B products made from mixed fibres and the price serve to
calculate the revenues. The costs depend on the produced amount of new wood fibres,
the produced amount of recycled fibres, the produced amount of P&B, the produced
waste in each production function, the operation costs and the depreciation. The
revenues and costs provide the cumulative profits of this new facility.
When the new facility produces P&B, the prices behave with a similar volatility
of the Dutch P&BI. However, the prices are lower to compete with the products of the
Dutch P&BI as explained in section 2.1.1: Production Process. The assumption is that
the new facility has a more efficient production process than the Dutch P&BI.
NF P&B Depreciation
NF PBB Recycing
Investment Budget Og
INF investment
NF Pas
Transformation
Investment Budget!
Consumption,
3
INF P&B Capital Stock
[New Facility P&B Capital Stock
)
NF
NF Variation of Price
per ton of
Revenues
Pee,
2B Annual
NF P&B Pulping
Waste
(Citra annuot cos
NF P&B Reafing INF Price per ton of P& NF PRB
Investment ghadget di NF P&B Recycling PR Transformation
Consumetfon B Waste Waste
NF P88 Depreciatio
NF Deprecation
Period F PAB PRB Sale:
NF Pas
‘Transformation
Investment Budget
Cy
NF P&B Pulping
Investment Budget
Now Facility P&B Investment
Transition
NF P&B Pulping
investment Buaget
Consumption
New Facility P&B Profits
NF P&B Commutative
‘Annual Profits
NF P&B Pulping
Nr Pep
‘Transformation P&B
INF P&B Operating
Costs
NF PAB Recycling PB
5
NF Pas Recycling
Expected Capacty
(
NF PBB Recyding
Current Expansion
NF P86 Pulping
expected Capacty
NF P&B Pulping
Current Expansion
NF Pee
‘Transformation
Expected Capacty
NF PAB
‘Transformation
Current Expansion
NF Pas Recycling
Current Capacity
‘New Facility P&B Capacity Adjustment
oS
oO
cure
NF Investment
NF P&B Pulping
Capacty
=]
NEPEB
Transformation
Current Capacky
NF PBB Pulpwood
Purchase
NF Pas Pulpwood
Rate
NF P&B Pulping %
Waste
NF P&B Pulping
Waste
NF Pae %
Recovered PAB
NF P&B Pulpwood Stock
c
NF P&B Pulping
INF P88 Recycing
Current Capactty
NF PAB Recycling PE
L @
NF P&B Pulping
turrent Capacty
NF P&B PRB Sales
x)
NF P&B PRB Stock
ie)
NF P&B Fibres Stock
NF P&B Recovered PEB
NF P&B Recovered
Foreign Recovered
PRB Ri
NEP
NF P&B Recyding % NF PAB Recying PA Transformation
ra)
‘Transformation %
Foreign Pas
Collection Rate
New Facility for P&B
Figure SM5: New Facility for Wood Pulp, Recycled Fibres and P&B
Table SM3 presents the model equations of the quantitative model of the new facilities,
ordered by element type.
Table SM3: Model equations of the new facilities
al Element Information
Type
‘Auxiliary | NF P&B Depreciation {autotype Real; autounit EUR/yr; def STEP('NF P&B Capital Stock'/'NF
Depreciation Period’, STARTTIME+20<<yr>>)}
‘Auxiliary | NF P&B Operating Costs {autotype Real; unit EUR/tn; def 285}
‘Auxiliary | NF P&B P&B Sales {autotype Real; autounit tn/yr; def 0*'NF P&B P&B Stock'/1<<yr>>}
Auxiliary | NF P&B Pulping % Waste {; autotype Real; def 0.25}
Auxiliary | NF P&B Pulping {autotype Real; autounit tn/yr; def STEP('NF P&B Pulping Current
Capacity’, STARTTIME+20<<yr>>)}
Auxiliary | NF P&B Pulping Current Expansion {autotype Real; autounit tn/yr?; def STEP((‘NF P&B Pulping
Expected Capacity’-'NF P&B Pulping Current Capacity')/'NF Investment Period',STARTTIME+16<<yr>>)}
Auxiliary | NF P&B Pulping Expected Capacity {autotype Real; unit tn/yr; def 35256}
Element
Element Information
Type
Auxiliary | NF P&B Pulping Investment Budget Consumption {autotype Real; autounit EUR/yr; def STEP(IF(NF
P&B Pulping Investment Budget'>0<<EUR>>,'NF P&B Pulping Investment Budget'/'NF Investment
Period',0<<EUR/yr>>),STARTTIME+16<<yr>>)}
‘Auxiliary | NF P&B Pulping Waste {autotype Real; autounit tn/yr; def STEP('NF P&B Pulping™'NF P&B Pulping %
Waste'/(1-'NF P&B Pulping % Waste’), STARTTIME+20<<yr>>)}
Auxiliary | NF P&B Pulpwood Purchase {autotype Real; unit tn/yr; def STEP(((1-NF P&B % Recovered P&B')*(‘NF
P&B Transformation Current Capacity'/(1-'NF P&B Transformation % Waste')))/'NF P&B Pulping %
Waste’, STARTTIME+20<<yr>>)}
Auxiliary | NF P&B Pulpwood Rate {autotype Real; autounit tn/yr; def 'NF P&B Pulpwood Purchase’}
Auxiliary | NF P&B Recovered Foreign Recovered P&B Rate {autotype Real; unit tn/yr; def MIN(IF((‘NF P&B
Requirement'-'NF P&B Recovered P&B Rate’)<0<<tn/yr>>,0<<tn/yr>>,('NF P&B Requirement'-'NF P&B
Recovered P&B Rate’)),'Foreign P&B Collection Rate')}
Auxiliary | NF P&B Recovered P&B Rate {autotype Real; autounit tn/yr; def MIN('NF P&B Requirement’,'NL
Recovered P&B Rate')}
‘Auxiliary | NF P&B Recycled % Waste {autotype Real; def 0.3; }
‘Auxiliary | NF P&B Recycled Annual Cost {autotype Real; autounit EUR/yr; def STEP(('NF P&B Recycled Operating
Costs’*('NF P&B Recycled Transformation P&B'+'NF P&B Recycled Recycling P&B'+'NF P&B Recycled
Transformation Waste'+'NF P&B Recycling Recycling P&B Waste’))+'NF P&B Recycled
Depreciation’, STARTTIME+20<<yr>>)}
Auxiliary | NF P&B Recycled Annual Revenues {autotype Real; autounit EUR/yr; def STEP('NF Price per ton of
P&B'*'NF P&B Recycling P&B Sales’ STARTTIME+20<<yr>>)}
‘Auxiliary | NF P&B Recycled Depreciation {autotype Real; autounit EUR/yr; def STEP('NF P&B Recycled Capital
Stock'/'NF Depreciation Period’ STARTTIME+20<<yr>>)}
‘Auxiliary | NF P&B Recycled Foreign Recovered P&B Rate {autotype Real; unit tn/yr; def MIN(IF(('NF P&B Recycled
Requirement'-NF P&B Recycled NL Recovered P&B Rate’)<0<<tn/yr>>,0<<tn/yr>>,('NF P&B Recycled
Requirement'-'NF P&B Recycled NL Recovered P&B Rate’)),'Foreign P&B Collection Rate’)}
Auxiliary | NF P&B Recycled Investment Budget Consumption {autotype Real; autounit EUR/yr; def STEP(IF(NF
P&B Recycled Recycling Investment Budget'>0<<EUR>>,'NF P&B; Recycled Recycling Investment
Budget’/'NF Investment Period',0<<EUR/yr>>),STARTTIME+16<<yr>>)}
‘Auxiliary | NF P&B Recycled NL Recovered P&B Rate {autotype Real; autounit tn/yr; def MIN('NF P&B Recycled
Requirement’, 'NL Recovered P&B Rate')}
Auxiliary | NF P&B Recycled Operating Costs {autotype Real; unit EUR/tn; def 285}
Auxiliary | NF P&B Recycled Recycling Current Expansion {autotype Real; autounit tn/yr2; def STEP((NF P&B
Recycled Recycling Expected Capacity'-'NF P&B Recycled Recycling Current Capacity')/'NF Investment
Period’, STARTTIME+16<<yr>>)}
‘Auxiliary | NF P&B Recycled Recycling Expected Capacity {autotype Real; unit tn/yr; def 150376}
‘Auxiliary | NF P&B Recycled Recycling P&B {autotype Real; autounit tn/yr; def STEP('NF P&B Recycled Recycling
Current Capacity’ STARTTIME+20<<yr>>)}
‘Auxiliary | NF P&B Recycled Requirement {autotype Real; unit tn/yr; def STEP((NF P&B Recycled Transformation
Current Capacity'//((1-'NF P&B Recycled % Waste’)*(1-'NF P&B Recycled Transformation %
Waste’))),STARTTIME+20<<yr>>)}
‘Auxiliary | NF P&B Recycled Transformation % Waste {autotype Real; def 0.05}
Auxiliary | NF P&B Recycled Transformation Current Expansion {autotype Real; autounit tn/yr2; def STEP(('NF
P&B Recycled Transformation Expected Capacity'-'NF P&B Recycled Transformation Current Capacity’)/'NF
Investment Period’ STARTTIME+16<<yr>>)}
Auxiliary | NF P&B Recycled Transformation Expected Capacity {autotype Real; unit tn/yr; def 100000}
‘Auxiliary | NF P&B Recycled Transformation Investment Budget Consumption {autotype Real; autounit EUR/yr;
def STEP(IF('NF P&B Recycled Transformation Investment Budget'>0<<EUR>>,'NF P&B Recycled
Transformation Investment Budget'/'NF Investment Period',0<<EUR/yr>>),STARTTIME+16<<yr>>)}
Auxiliary | NF P&B Recycled Transformation P&B {autotype Real; autounit tn/yr; def STEP('NF P&B Recycled
Transformation Current Capacity’, STARTTIME+20<<yr>>)}
‘Auxiliary | NF P&B Recycled Transformation Waste {autotype Real; autounit tn/yr; def STEP('NF P&B Recycled
Transformation P&B™'NF P&B Recycled Transformation % Waste'/(1-'NF P&B Recycled Transformation %
Waste’), STARTTIME+20<<yr>>)}
Auxiliary | NF P&B Recycling % Waste {autotype Real; def 0.3}
Auxiliary | NF P&B Recycling Current Expansion {autotype Real; autounit tn/yr2; def STEP(('NF P&B Recycling
Expected Capacity'-'NF P&B Recycling Current Capacity’)/'NF Investment
Period’, STARTTIME+16<<yr>>)}
Auxiliary
NF P&B Recycling Expected Capacity {autotype Real; unit tn/yr; def 112602}
Element
Element Information
Type
Auxiliary | NF P&B Recycling Investment Budget Consumption {autotype Real; autounit EUR/yr; def STEP(IF(NF
P&B Recycling Investment Budget'>0<<EUR>>,'NF P&B Recycling Investment Budget'/'NF Investment
Period’,0<<EUR/yr>>),STARTTIME+16<<yr>>)}
Auxiliary | NF P&B Recycling P&B {autotype Real; autounit tn/yr; def STEP('NF P&B Recycling Current
Capacity’ STARTTIME+20<<yr>>)}
Auxiliary | NF P&B Recycling P&B Sales {autotype Real; autounit tn/yr; def O*'NF P&B Recycled P&B
Stock'/1<<yr>>}
Auxiliary | NF P&B Recycling P&B Waste {autotype Real; autounit tn/yr; def STEP('NF P&B Recycling P&B™'NF
P&B Recycling % Waste’/(1-'NF P&B Recycling % Waste’), STARTTIME+20<<yr>>)}
‘Auxiliary | NF P&B Recycling Recycling P&B Waste {autotype Real; autounit tn/yr; def STEP('NF P&B Recycled
Recycling P&B™*'NF P&B Recycled % Waste’/(1-'NF P&B Recycled % Waste’), STARTTIME+20<<yr>>)}
Auxiliary | NF P&B Requirement {autotype Real; unit tn/yr; def STEP(('NF P&B % Recovered P&B™*('NF P&B
Transformation Current Capacity'/(1-'NF P&B Transformation % Waste’)))/'NF P&B Recycling %
Waste’, STARTTIME+20<<yr>>)}
Auxiliary | NF P&B Transformation % Waste {autotype Real; def 0.05}
Auxiliary | NF P&B Transformation Current Expansion {autotype Real; autounit tn/yr2; def STEP((NF P&B
Transformation Expected Capacity'-'NF P&B Transformation Current Capacity')/'NF Investment
Period’, STARTTIME+16<<yr>>)}
‘Auxiliary | NF P&B Transformation Expected Capacity {autotype Real; unit tn/yr; def 100000 }
Auxiliary | NF P&B Transformation Investment Budget Consumption {autotype Real; autounit EUR/yr; def
STEP(IF('NF P&B Transformation Investment Budget'>0<<EUR>>,'NF P&B Transformation Investment
Budget’/'NF Investment Period',0<<EUR/yr>>), STARTTIME+16<<yr>>)}
Auxiliary | NF P&B Transformation P&B {autotype Real; autounit tn/yr; def 'NF P&B Transformation Current
Capacity'}
Auxiliary | NF P&B Transformation Waste {autotype Real; autounit tn/yr; def STEP('NF P&B Transformation
P&B™*'NF P&B Transformation % Waste'/(1-'NF P&B Transformation % Waste’), STARTTIME+20<<yr>>)}
Auxiliary | NF P&B Wood Pulp Annual Cost {autotype Real; autounit EUR/yr; def STEP(('NF P&B Wood Pulp
Operating Costs"*('NF P&B Wood Pulp Transformation'+'NF P&B Wood Pulp Pulping'+'NF P&B Wood Pulp
Pulping Waste'+'NF P&B Wood Pulp Transformation Waste’))+'NF P&B Wood Pulp
Depreciation’, STARTTIME+20<<yr>>)}
Auxiliary | NF P&B Wood Pulp Annual Revenues {autotype Real; autounit EUR/yr; def STEP('NF Price per ton of
P&B'*'NF P&B Wood Pulp P&B Sales’ STARTTIME+20<<yr>>)}
‘Auxiliary | NF P&B Wood Pulp Depreciation {autotype Real; autounit EUR/yr; def STEP(‘NF P&B Wood Pulp Capital
Stock'/'NF Depreciation Period’ STARTTIME+20<<yr>>)}
Auxiliary | NF P&B Wood Pulp Operating Costs {autotype Real; unit EUR/tn; def 285}
Auxiliary | NF P&B Wood Pulp P&B Sales {autotype Real; autounit tn/yr; def 0*'NF P&B Wood Pulp P&B
Stock'/1<<yr>>}
Auxiliary | NF P&B Wood Pulp Pulping % Waste {autotype Real; def 0.25}
Auxiliary | NF P&B Wood Pulp Pulping {autotype Real; autounit tn/yr; def STEP('NF P&B Wood Pulp Pulping
Current Capacity’ STARTTIME+20<<yr>>)}
‘Auxiliary | NF P&B Wood Pulp Pulping Current Expansion {autotype Real; autounit tn/yr2; def STEP((‘NF P&B
Wood Pulp Pulping Expected Capacity'-'NF P&B Wood Pulp Pulping Current Capacity’)/'NF Investment
Period’, STARTTIME+16<<yr>>)}
Auxiliary | NF P&B Wood Pulp Pulping Expected Capacity {autotype Real; unit tn/yr; def 140351}
Auxiliary | NF P&B Wood Pulp Pulping Investment Budget Consumption {autotype Real; autounit EUR/yr; def
STEP('NF P&B Wood Pulp Pulping Investment Budget'/'NF Investment Period',STARTTIME+20<<yr>>)}
Auxiliary | NF P&B Wood Pulp Pulping Waste {autotype Real; autounit tn/yr; def STEP('NF P&B Wood Pulp
Pulping’'NF P&B Wood Pulp Pulping % Waste'/(1-'NF P&B Wood Pulp Pulping %
Waste’), STARTTIME+20<<yr>>)}
Auxiliary | NF P&B Wood Pulp Pulpwood Purchase {autotype Real; unit tn/yr; def STEP(('NF P&B Wood Pulp
Transformation Current Capacity'/((1-'NF P&B Wood Pulp Pulping % Waste')*(1-'NF P&B Wood Pulp
Transformation % Waste'))), STARTTIME+20<<yr>>)}
Auxiliary | NF P&B Wood Pulp Pulpwood Rate {autotype Real; autounit tn/yr; def STEP('NF P&B Wood Pulp
Pulpwood Purchase’, STARTTIME+20<<yr>>)}
Auxiliary | NF P&B Wood Pulp Transformation % Waste {autotype Real; def 0.05}
Auxiliary | NF P&B Wood Pulp Transformation {autotype Real; autounit tn/yr; def STEP('NF P&B Wood Pulp
Transformation Current Capacity’, STARTTIME+20<<yr>>)}
Auxiliary | NF P&B Wood Pulp Transformation Current Expansion {autotype Real; autounit tn/yr2; def STEP((‘NF
P&B Wood Pulp Transformation Expected Capacity'-'NF P&B Wood Pulp}
Element
Element Information
Type
‘Auxiliary | NF P&B Wood Pulp Transformation Expected Capacity {autotype Real; unit tn/yr; def 100000}
‘Auxiliary | NF P&B Wood Pulp Transformation Investment Budget Consumption {autotype Real; autounit EUR/yr;
def STEP(IF('NF P&B Wood Pulp Transformation Investment Budget'>0<<EUR>>,'NF P&B Wood Pulp
Transformation Investment Budget'/'NF Investment Period',0<<EUR/yr>>),STARTTIME+16<<yr>>)}
Auxiliary | NF P&B Wood Pulp Transformation Waste {autotype Real; autounit tn/yr; def STEP('NF P&B Wood Pulp
Transformation*'NF P&B Wood Pulp Transformation % Waste’/(1-'NF P&B Wood Pulp Transformation %
Waste’), STARTTIME+20<<yr>>)}
Auxiliary | NF Recycled % Waste {autotype Real; def 0.3}
Auxiliary | NF Recycled Fibres Annual Cost {autotype Real; autounit EUR/yr; def STEP(('NF Recycled Fibres
Operating Costs’*('NF_ Recycling P&B'+'NF Recycling P&B Waste’))+'NF Recycling P&B
Depreciation’, STARTTIME+20<<yr>>)}
Auxiliary | NF Recycled Fibres Annual Revenues {autotype Real; autounit EUR/yr; def STEP('NF Recycled Fibres
Price*'NF Recycled Fibres Sales',STARTTIME+20<<yr>>}
‘Auxiliary | NF Recycled Fibres Foreign Recovered P&B Rate {autotype Real; unit tn/yr; def MIN(IF(('NF Recycled
Fibres Recovered P&B —Requirement'-'NF Recycled Fibres. += NL Recovered += P&B
Rate')<0<<tn/yr>>,0<<tn/yr>>, (‘NF Recycled Fibres Recovered P&B Requirement!-'NF Recycled Fibres
NL Recovered P&B Rate’)),'Foreign P&B Collection Rate’)}
‘Auxiliary | NF Recycled Fibres NL Recovered P&B Rate {autotype Real; autounit tn/yr; def MIN('NF Recycled
Fibres Recovered P&B Requirement’, 'NL Recovered P&B Rate’)}
Auxiliary | NF Recycled Fibres Operating Costs {autotype Real; unit EUR/tn; def 285}
‘Auxiliary | NF Recycled Fibres Price {autotype Real; unit EUR/tn; def 380}
Auxiliary | NF Recycled Fibres Recovered P&B Requirement {autotype Real; unit tn/yr; def STEP(('NF Recycling
P&B Current Capacity'/(1-'NF Recycled % Waste’), STARTTIME+20<<yr>>)}
Auxiliary | NF Recycled Fibres Sales {autotype Real; autounit tn/yr; def 0*'NF Recycled Fibres Stock'/1<<yr>>}
Auxiliary | NF Recycling P&B {autotype Real; autounit tn/yr; def STEP(NF Recycling P&B Current
Capacity’, STARTTIME+20<<yr>>)}
Auxiliary | NF Recycling P&B Current Expansion {autotype Real; autounit tn/yr2; def STEP(('NF Recycling P&B
Expected Capacity'-'NF Recycling P&B Current Capacity’)/'NF Investment
Period’, STARTTIME+16<<yr>>)}
‘Auxiliary | NF Recycling P&B Depreciation {autotype Real; autounit EUR/yr; def STEP('NF Recycling P&B Capital
Stock'/'NF Depreciation Period’ STARTTIME+20<<yr>>)}
Auxiliary | NF Recycling P&B Expected Capacity {autotype Real; unit tn/yr; def 350000; }
‘Auxiliary | NF Recycling P&B Investment Budget Consumption {autotype Real; autounit EUR/yr; def STEP(IF(NF
Recycling P&B Investment Budget'>0<<EUR>>,'NF Recycling P&B Investment Budget'/'NF Investment
Period’,0<<EUR/yr>>),STARTTIME+16<<yr>>)}
Auxiliary | NF Recycling P&B Waste {autotype Real; autounit tn/yr; def STEP('NF Recycling P&B*'NF Recycled %
Waste'/(1-'NF Recycled % Waste’), STARTTIME+20<<yr>>)}
Auxiliary | NF Variation of Price per ton of P&B {autotype Real; autounit EUR/(yr*tn); def
STEP(10<<EUR/(tn*yr)>>+2.5<<EUR/(tn*yr)>>*COSWAVE(25,5<<yr>>,3.5<<yr>>),
STARTTIME+20<<yr>>)}
Auxiliary | NF Wood Pulp % Waste {autotype Real; def 0.25}
‘Auxiliary | NF Wood Pulp Annual Cost {autotype Real; autounit EUR/yr; def STEP(('NF Wood Pulp Operating
Costs’*('NF Wood Pulp Transformation'+'NF_ Wood Pulp Waste’))+'NF_ Wood Pulp
Depreciation’, STARTTIME+20<<yr>>)}
Auxiliary | NF Wood Pulp Annual Revenues {autotype Real; autounit EUR/yr; def STEP('NF Wood Pulp Price*NF
Wood Pulp Sales’ STARTTIME+20<<yr>>)}
‘Auxiliary | NF Wood Pulp Current Expansion {autotype Real; autounit tn/yr2; def STEP(('NF Wood Pulp Expected
Capacity'-'NF Wood Pulp Current Capacity’)/'NF Investment Period’ STARTTIME+16<<yr>>)}
‘Auxiliary | NF Wood Pulp Depreciation {autotype Real; autounit EUR/yr; def STEP('NF Wood Pulp Capital
Stock'/'NF Depreciation Period’ STARTTIME+20<<yr>>)}
Auxiliary | NF Wood Pulp Expected Capacity {autotype Real; unit tn/yr; def 350000}
‘Auxiliary | NF Wood Pulp Investment Budget Consumption {autotype Real; autounit EUR/yr; def STEP('NF Wood
Pulp Investment Budget'/'NF Investment Period’ STARTTIME+16<<yr>>)}
‘Auxiliary | NF Wood Pulp Operating Costs {autotype Real; unit EUR/tn; def 285}
‘Auxiliary | NF Wood Pulp Price {autotype Real; unit EUR/tn; def 500}
Auxiliary | NF Wood Pulp Pulpwood Purchase {autotype Real; unit tn/yr; def STEP(('NF Wood Pulp Current
Capacity'/(1-'NF Wood Pulp % Waste’)), STARTTIME+20<<yr>>)}
Element
Element Information
Type
‘Auxiliary | NF Wood Pulp Pulpwood Rate {autotype Real; autounit tn/yr; def STEP('NF Wood Pulp Pulpwood
Purchase’ STARTTIME+20<<yr>>)}
Auxiliary | NF Wood Pulp Sales {autotype Real; autounit tn/yr; def STEP(NF Wood Pulp
Stock'/0.04<<yr>>,STARTTIME+20.01<<yr>>)}
Auxiliary | NF Wood Pulp Transformation {autotype Real; autounit tn/yr; def STEP(NF Wood Pulp Current
Capacity’, STARTTIME+20<<yr>>)}
Auxiliary | NF Depreciation Period {autotype Real; unit yr; def 25}
NF Investment Period {autotype Real; unit yr; def 4}
NF P&B % Recovered P&B {autotype Real; def 0.7488}
NF P&B Annual Cost {autotype Real; autounit EUR/yr; def STEP(('‘NF P&B Operating Costs’*('NF P&B
Transformation P&B'+'NF P&B Pulping'+'NF P&B Recycling P&B'+'NF P&B Pulping Waste'+'NF P&B
Recycling P&B Waste'+'NF P&B Transformation Waste’))+'NF P&B Depreciation’, STARTTIME+20<<yr>>}
Auxiliary
NF P&B Annual Revenues {autotype Real; autounit EUR/yr; def STEP('NF Price per ton of P&B™'NF P&B
P&B Sales’, STARTTIME+20<<yr>>)}
Level
NF P&B Recycling Current Capacity {autotype Real; unit tn/yr; init 0; inflow { autodef 'NF P&B
Recycling Current Expansion’ }}
Level
NF P&B Transformation Current Capacity {autotype Real; unit tn/yr; init 0; inflow { autodef 'NF P&B
Transformation Current Expansion’ }}
Level
NF P&B Capital Stock {autotype Real; unit EUR; init 0; inflow { autodef ‘NF P&B Recycling Investment
Budget Consumption’ }; outflow { autodef 'NF P&B Depreciation’ }; inflow { autodef 'NF P&B
Transformation Investment Budget Consumption’ }; inflow { autodef 'NF P&B Pulping Investment
Budget Consumption’ }}
Level
NF P&B Cumulative Annual Profits {autotype Real; unit EUR;
Revenues’ }; outflow { autodef 'NF P&B Annual Cost’ }}
0; inflow { autodef 'NF P&B Annual
Level
NF P&B Fibres Stock {autotype Real; unit tn; init 0; inflow { autodef 'NF P&B Recycling P&B" };
outflow { autodef 'NF P&B Transformation P&B' }; outflow { autodef 'NF P&B Transformation Waste’
}; inflow { autodef ‘NF P&B Pulping’ }}
Level
NF P&B P&B Stock {; autotype Real; unit tn; init 0; outflow { autodef 'NF P&B P&B Sales’ }; inflow {
autodef 'NF P&B Transformation P&B' }}
Level
NF P&B Pulping Current Capacity {autotype Real; unit tn/yr; init 0; inflow { autodef 'NF P&B Pulping
Current Expansion’ }}
Level
NF P&B Pulping Investment Budget {autotype Real; unit EUR; init 57338835; outflow { autodef ‘NF
P&B Pulping Investment Budget Consumption’ }}
Level
NF P&B Pulpwood Stock {autotype Real; unit tn; init 0; inflow { autodef 'NF P&B Pulpwood Rate’ };
outflow { autodef 'NF P&B Pulping’ }; outflow { autodef 'NF P&B Pulping Waste’ }}
Level
NF P&B Recovered P&B Stock {autotype Real; unit tn; init 0; inflow { autodef 'NF P&B Recovered P&B
Rate’ }; outflow { autodef 'NF P&B Recycling P&B’ }; inflow { autodef 'NF P&B Recovered Foreign
Recovered P&B Rate’ }; outflow { autodef 'NF P&B Recycling P&B Waste' }}
Level
NF P&B Recycled Capital Stock {autotype Real; unit EUR; init 0; inflow { autodef 'NF P&B Recycled
Investment Budget Consumption’ }; outflow { autodef 'NF P&B Recycled Depreciation’ }; inflow {
autodef 'NF P&B Recycled Transformation Investment Budget Consumption’}}
Level
NF P&B Recycled Cumulative Annual Profits {autotype Real; unit EUR; init 0; inflow { autodef 'NF P&B
Recycled Annual Revenues’ }; outflow { autodef 'NF P&B Recycled Annual Cost’ }}
Level
NF P&B Recycled Fibres Stock {autotype Real; unit tn; init 0; inflow { autodef 'NF P&B Recycled
Recycling P&B' }; outflow { autodef 'NF P&B Recycled Transformation P&B' }; outflow { autodef 'NF
P&B Recycled Transformation Waste’ }}
Level
NF P&B Recycled P&B Stock {autotype Real; unit tn; init 0; outflow { autodef 'NF P&B Recycling P&B
Sales' }; inflow { autodef 'NF P&B Recycled Transformation P&B }}
Level
NF P&B Recycled Recovered P&B Stock {autotype Real; unit tn; init 0; inflow { autodef 'NF P&B
Recycled NL Recovered P&B Rate’ }; outflow { autodef 'NF P&B Recycled Recycling P&B' }; inflow {
autodef 'NF P&B Recycled Foreign Recovered P&B Rate’ }; outflow { autodef 'NF P&B Recycling
Recycling P&B Waste’ }}
Level
NF P&B Recycled Recycling Current Capacity {autotype Real; unit tn/yr; init 0; inflow { autodef 'NF
P&B Recycled Recycling Current Expansion’ }}
Level
NF P&B Recycled Recycling Investment Budget {autotype Real; unit EUR; init 114081152; outflow {
autodef 'NF P&B Recycled Investment Budget Consumption’ }}
Level
NF P&B Recycled Transformation Current Capacity {autotype Real; unit tn/yr; init 0; inflow { autodef
'NF P&B Recycled Transformation Current Expansion’ }}
Element
Element Information
Type
Level NF P&B Recycled Transformation Investment Budget {autotype Real; unit EUR; init 191184094;
outflow { autodef 'NF P&B Recycled Transformation Investment Budget Consumption’ }}
Level NF P&B Recycling Investment Budget {autotype Real; unit EUR; init 94526089; outflow { autodef 'NF
P&B Recycling Investment Budget Consumption’ }}
Level NF P&B Transformation Investment Budget {autotype Real; unit EUR; init 191184094; outflow {
autodef 'NF P&B Transformation Investment Budget Consumption’ }}
Level NF P&B Wood Pulp Capital Stock {autotype Real; unit EUR; init 0; inflow { autodef 'NF P&B Wood
Pulp Pulping Investment Budget Consumption’ }; outflow { autodef 'NF P&B Wood Pulp Depreciation’ };
inflow { autodef 'NF P&B Wood Pulp Transformation Investment Budget Consumption’ }}
Level NF P&B Wood Pulp Cumulative Annual Profits {autotype Real; unit EUR; init 0; inflow { autodef 'NF
P&B Wood Pulp Annual Revenues’ }; outflow { autodef 'NF P&B Wood Pulp Annual Cost! }}
Level NF P&B Wood Pulp Fibres Stock {autotype Real; unit tn; init 0; inflow { autodef 'NF P&B Wood Pulp
Pulping' }; outflow { autodef 'NF P&B Wood Pulp Transformation’ }; outflow { autodef 'NF P&B Wood
Pulp Transformation Waste’ }}
Level NF P&B Wood Pulp P&B Stock {autotype Real; unit tn; init 0; outflow { autodef 'NF P&B Wood Pulp
P&B Sales’ }; inflow { autodef 'NF P&B Wood Pulp Transformation’ }}
Level NF P&B Wood Pulp Pulping Current Capacity {autotype Real; unit tn/yr; init 0; inflow { autodef 'NF
P&B Wood Pulp Pulping Current Expansion’ }}
Level NF P&B Wood Pulp Pulping Investment Budget {autotype Real; unit EUR; init 140746013; outflow {
autodef 'NF P&B Wood Pulp Pulping Investment Budget Consumption’ }}
Level NF P&B Wood Pulp Pulpwood Stock {autotype Real; unit tn; init 0; inflow { autodef 'NF P&B Wood
Pulp Pulpwood Rate’ }; outflow { autodef 'NF P&B Wood Pulp Pulping' }; outflow { autodef 'NF P&B
Wood Pulp Pulping Waste’ }}
Level NE P&B Wood Pulp Transformation Current Capacity {autotype Real; unit tn/yr; init 0; inflow {
autodef 'NF P&B Wood Pulp Transformation Current Expansion’ }}
Level NF P&B Wood Pulp Transformation Investment Budget {autotype Real; unit EUR; init 191184094;
outflow { autodef 'NF P&B Wood Pulp Transformation Investment Budget Consumption’ }}
Level NF Price per ton of P&B {autotype Real; unit EUR/tn; init 550; inflow { autodef 'NF Variation of Price
per ton of P&B' }}
Level NF Recovered P&B Stock {autotype Real; unit tn; init 96000; inflow { autodef 'NF Recycled Fibres NL
Recovered P&B Rate’ }; outflow { autodef 'NF Recycling P&B' }; inflow { autodef 'NF Recycled Fibres
Foreign Recovered P&B Rate’ }; outflow { autodef ‘NF Recycling P&B Waste’ }}
Level NF Recycled Fibres Cumulative Annual Profits {autotype Real; unit EUR; init 0; inflow { autodef 'NF
Recycled Fibres Annual Revenues’ }; outflow { autodef 'NF Recycled Fibres Annual Cost! }}
Level NF Recycled Fibres Stock {autotype Real; unit tn; init 0; inflow { autodef 'NF Recycling P&B };
outflow { autodef 'NF Recycled Fibres Sales’ }}
Level NF Recycling P&B Capital Stock {autotype Real; unit EUR; init 0; inflow { autodef 'NF Recycling P&B
Investment Budget Consumption’ }; outflow { autodef 'NF Recycling P&B Depreciation’ }}
Level NF Recycling P&B Current Capacity {autotype Real; unit tn/yr; init 0; inflow { autodef 'NF Recycling
P&B Current Expansion’ }}
Level NF Recycling P&B Investment Budget {autotype Real; unit EUR; init 197556897; outflow { autodef
'NF Recycling P&B Investment Budget Consumption’ }}
Level NF Wood Pulp Capital Stock {autotype Real; unit EUR; init 0; inflow { autodef 'NF Wood Pulp
Investment Budget Consumption’ }; outflow { autodef 'NF Wood Pulp Depreciation’ }}
Level NF Wood Pulp Cumulative Annual Profits {autotype Real; unit EUR; init 0; inflow { autodef 'NF Wood
Pulp Annual Revenues’ }; outflow { autodef ‘NF Wood Pulp Annual Cost’ }}
Level NF Wood Pulp Current Capacity {autotype Real; unit tn/yr; init 0; inflow { autodef 'NF Wood Pulp
Current Expansion’ }}
Level NF Wood Pulp Investment Budget {autotype Real; unit EUR; init 254912125; outflow { autodef 'NF
Wood Pulp Investment Budget Consumption’ }}
Level NF Wood Pulp Pulpwood Stock {autotype Real; unit tn; init 96000; inflow { autodef 'NF Wood Pulp
Pulpwood Rate’ }; outflow { autodef 'NF Wood Pulp Transformation’ }; outflow { autodef 'NF Wood
Pulp Waste’ }}
Level NF Wood Pulp Stock {autotype Real; unit tn; init 0; inflow { autodef 'NF Wood Pulp Transformation’
}; outflow { autodef ‘NF Wood Pulp Sales’ }}
